Instantaneous network model diagnostics - balanced statistics

This file shows diagnostics for instantaneous network models fit using balanced racial/ethnic mixing matrices and degree terms adjusted to correspond to the balanced mixing matrices. In this file, we fit a series of nested models by adding one term at a time to examine changes to model estimates, MCMC diagnostics, and network diagnostics.

Load packages and model fits

rm(list = ls())
suppressMessages(library("EpiModelHIV"))
library("latticeExtra")
## Loading required package: lattice
## Loading required package: RColorBrewer
library("knitr")
library("kableExtra")

load(file = "/homes/dpwhite/R/GitHub Repos/WHAMP/Model fits and simulations/Fit tests and debugging/est/fit.i.buildup.bal.rda")

Model terms and control settings

Model terms and target statistics
Terms Model 1 Model 2 Model 3 Model 4 Model 5 Model 6 Model 7 Model 8
edges 479.2 479.2 479.2 479.2 479.2 479.2 479.2 479.2
nodefactor.deg.main.deg.pers.0.1 NA NA NA 172.3 172.3 172.3 172.3 172.3
nodefactor.deg.main.deg.pers.0.2 NA NA NA 36.4 36.4 36.4 36.4 36.4
nodefactor.deg.main.deg.pers.1.0 NA NA NA 38.0 38.0 38.0 38.0 38.0
nodefactor.deg.main.deg.pers.1.1 NA NA NA 135.5 135.5 135.5 135.5 135.5
nodefactor.deg.main.deg.pers.1.2 NA NA NA 145.4 145.4 145.4 145.4 145.4
nodefactor.riskg.O1 NA NA NA NA NA NA 0.0 0.0
nodefactor.riskg.O2 NA NA NA NA NA NA 0.0 0.0
nodefactor.riskg.O3 NA NA NA NA NA NA 6.9 6.9
nodefactor.riskg.O4 NA NA NA NA NA NA 109.5 109.5
nodefactor.riskg.Y1 NA NA NA NA NA NA 0.0 0.0
nodefactor.riskg.Y2 NA NA NA NA NA NA 8.2 8.2
nodefactor.riskg.Y3 NA NA NA NA NA NA 70.8 70.8
nodefactor.race..wa.B NA 75.6 75.6 75.6 75.6 75.6 75.6 75.6
nodefactor.race..wa.H NA 149.2 149.2 149.2 149.2 149.2 149.2 149.2
nodefactor.region.EW NA NA NA NA 83.5 83.5 83.5 83.5
nodefactor.region.OW NA NA NA NA 242.5 242.5 242.5 242.5
nodematch.race..wa.B NA NA 2.5 2.5 2.5 2.5 2.5 2.5
nodematch.race..wa.H NA NA 13.3 13.3 13.3 13.3 13.3 13.3
nodematch.race..wa.O NA NA 286.9 286.9 286.9 286.9 286.9 286.9
nodematch.region NA NA NA NA NA NA NA 383.3
absdiff.sqrt.age NA NA NA NA NA 380.5 380.5 380.5
nodematch.role.class.I -Inf -Inf -Inf -Inf -Inf -Inf -Inf -Inf
nodematch.role.class.R -Inf -Inf -Inf -Inf -Inf -Inf -Inf -Inf

The control settings for these models are:

set.control.ergm = control.ergm(MCMC.interval = 1e+5,
                                MCMC.samplesize = 7500,
                                MCMC.burnin = 1e+6,
                                MPLE.max.dyad.types = 1e+7,
                                MCMLE.maxit = 400,
                                parallel = np/2, 
                                parallel.type="PSOCK"))

MCMC diagnostics

Model 1

## Sample statistics summary:
## 
## Iterations = 1e+06:375900000
## Thinning interval = 1e+05 
## Number of chains = 8 
## Sample size per chain = 3750 
## 
## 1. Empirical mean and standard deviation for each variable,
##    plus standard error of the mean:
## 
##           Mean             SD       Naive SE Time-series SE 
##         1.8838        21.6899         0.1252         0.1239 
## 
## 2. Quantiles for each variable:
## 
##    2.5%     25%     50%     75%   97.5% 
## -40.159 -13.159   1.841  16.841  44.841 
## 
## 
## Sample statistics cross-correlations:
##       edges
## edges     1
## 
## Sample statistics auto-correlation:
## Chain 1 
##                  edges
## Lag 0      1.000000000
## Lag 1e+05  0.021332915
## Lag 2e+05  0.002669399
## Lag 3e+05 -0.004888273
## Lag 4e+05  0.011901587
## Lag 5e+05  0.011800576
## Chain 2 
##                  edges
## Lag 0      1.000000000
## Lag 1e+05  0.013242592
## Lag 2e+05  0.016382186
## Lag 3e+05 -0.020064087
## Lag 4e+05  0.002296841
## Lag 5e+05  0.009784449
## Chain 3 
##                   edges
## Lag 0      1.0000000000
## Lag 1e+05 -0.0091597100
## Lag 2e+05 -0.0005450508
## Lag 3e+05 -0.0119443121
## Lag 4e+05 -0.0252038444
## Lag 5e+05 -0.0465869881
## Chain 4 
##                   edges
## Lag 0      1.0000000000
## Lag 1e+05 -0.0194879913
## Lag 2e+05  0.0157836779
## Lag 3e+05 -0.0235470441
## Lag 4e+05 -0.0283273184
## Lag 5e+05  0.0005466337
## Chain 5 
##                  edges
## Lag 0      1.000000000
## Lag 1e+05  0.008267646
## Lag 2e+05 -0.004205927
## Lag 3e+05  0.011081478
## Lag 4e+05  0.005215142
## Lag 5e+05  0.002653280
## Chain 6 
##                  edges
## Lag 0      1.000000000
## Lag 1e+05  0.000403967
## Lag 2e+05 -0.019047133
## Lag 3e+05  0.028459673
## Lag 4e+05  0.021563362
## Lag 5e+05  0.005491952
## Chain 7 
##                  edges
## Lag 0      1.000000000
## Lag 1e+05  0.005402465
## Lag 2e+05 -0.008740617
## Lag 3e+05  0.020281924
## Lag 4e+05 -0.021406586
## Lag 5e+05 -0.006723432
## Chain 8 
##                   edges
## Lag 0      1.0000000000
## Lag 1e+05 -0.0056448333
## Lag 2e+05  0.0066092961
## Lag 3e+05 -0.0005693126
## Lag 4e+05  0.0257470120
## Lag 5e+05 -0.0035451231
## 
## Sample statistics burn-in diagnostic (Geweke):
## Chain 8 
## 
## Fraction in 1st window = 0.1
## Fraction in 2nd window = 0.5 
## 
##  edges 
## 0.3158 
## 
## Individual P-values (lower = worse):
##     edges 
## 0.7521337 
## Joint P-value (lower = worse):  0.7481276 .
## Chain 8 
## 
## Fraction in 1st window = 0.1
## Fraction in 2nd window = 0.5 
## 
## edges 
## 0.163 
## 
## Individual P-values (lower = worse):
##    edges 
## 0.870489 
## Joint P-value (lower = worse):  0.8762538 .
## Chain 8 
## 
## Fraction in 1st window = 0.1
## Fraction in 2nd window = 0.5 
## 
##  edges 
## 0.7798 
## 
## Individual P-values (lower = worse):
##     edges 
## 0.4354886 
## Joint P-value (lower = worse):  0.3953077 .
## Chain 8 
## 
## Fraction in 1st window = 0.1
## Fraction in 2nd window = 0.5 
## 
##   edges 
## -0.3549 
## 
## Individual P-values (lower = worse):
##    edges 
## 0.722691 
## Joint P-value (lower = worse):  0.7295304 .
## Chain 8 
## 
## Fraction in 1st window = 0.1
## Fraction in 2nd window = 0.5 
## 
##  edges 
## 0.6891 
## 
## Individual P-values (lower = worse):
##     edges 
## 0.4907354 
## Joint P-value (lower = worse):  0.416782 .
## Chain 8 
## 
## Fraction in 1st window = 0.1
## Fraction in 2nd window = 0.5 
## 
##  edges 
## 0.9951 
## 
## Individual P-values (lower = worse):
##     edges 
## 0.3196815 
## Joint P-value (lower = worse):  0.3223314 .
## Chain 8 
## 
## Fraction in 1st window = 0.1
## Fraction in 2nd window = 0.5 
## 
## edges 
## 0.205 
## 
## Individual P-values (lower = worse):
##     edges 
## 0.8376064 
## Joint P-value (lower = worse):  0.8382153 .
## Chain 8 
## 
## Fraction in 1st window = 0.1
## Fraction in 2nd window = 0.5 
## 
##  edges 
## 0.5326 
## 
## Individual P-values (lower = worse):
##     edges 
## 0.5942949 
## Joint P-value (lower = worse):  0.5886258 .
## Warning in formals(fun): argument is not a function

## 
## MCMC diagnostics shown here are from the last round of simulation, prior to computation of final parameter estimates. Because the final estimates are refinements of those used for this simulation run, these diagnostics may understate model performance. To directly assess the performance of the final model on in-model statistics, please use the GOF command: gof(ergmFitObject, GOF=~model).

Model 2

## Sample statistics summary:
## 
## Iterations = 1e+06:375900000
## Thinning interval = 1e+05 
## Number of chains = 8 
## Sample size per chain = 3750 
## 
## 1. Empirical mean and standard deviation for each variable,
##    plus standard error of the mean:
## 
##                           Mean     SD Naive SE Time-series SE
## edges                  0.83031 21.851  0.12615        0.12557
## nodefactor.race..wa.B -0.07032  9.057  0.05229        0.05221
## nodefactor.race..wa.H -0.27285 13.152  0.07593        0.07617
## 
## 2. Quantiles for each variable:
## 
##                         2.5%     25%     50%    75% 97.5%
## edges                 -42.16 -14.159  0.8414 15.841 43.84
## nodefactor.race..wa.B -17.59  -6.591 -0.5908  5.409 18.41
## nodefactor.race..wa.H -25.17  -9.174 -0.1739  8.826 25.83
## 
## 
## Sample statistics cross-correlations:
##                           edges nodefactor.race..wa.B
## edges                 1.0000000             0.3822744
## nodefactor.race..wa.B 0.3822744             1.0000000
## nodefactor.race..wa.H 0.5184546             0.1044710
##                       nodefactor.race..wa.H
## edges                             0.5184546
## nodefactor.race..wa.B             0.1044710
## nodefactor.race..wa.H             1.0000000
## 
## Sample statistics auto-correlation:
## Chain 1 
##                  edges nodefactor.race..wa.B nodefactor.race..wa.H
## Lag 0      1.000000000           1.000000000          1.0000000000
## Lag 1e+05  0.001010140          -0.019467684         -0.0091849257
## Lag 2e+05 -0.013309993           0.035413701          0.0081303469
## Lag 3e+05 -0.012150594          -0.028372853         -0.0063887810
## Lag 4e+05  0.001022307           0.009074304          0.0103598879
## Lag 5e+05 -0.007844441          -0.002531519          0.0006497536
## Chain 2 
##                  edges nodefactor.race..wa.B nodefactor.race..wa.H
## Lag 0      1.000000000           1.000000000          1.0000000000
## Lag 1e+05  0.012339381          -0.001678819          0.0241005868
## Lag 2e+05 -0.012337337          -0.020303192         -0.0147918322
## Lag 3e+05 -0.017094795          -0.016690382          0.0388980665
## Lag 4e+05  0.014955208          -0.024040245         -0.0077695262
## Lag 5e+05 -0.008166303          -0.019730742          0.0006704216
## Chain 3 
##                  edges nodefactor.race..wa.B nodefactor.race..wa.H
## Lag 0      1.000000000           1.000000000           1.000000000
## Lag 1e+05 -0.034933666          -0.019433867          -0.013702963
## Lag 2e+05 -0.013711447          -0.002375690          -0.002330164
## Lag 3e+05  0.036875720           0.030341706           0.002544738
## Lag 4e+05 -0.013010745           0.004498821          -0.042817338
## Lag 5e+05 -0.006653495          -0.009852775           0.019762354
## Chain 4 
##                  edges nodefactor.race..wa.B nodefactor.race..wa.H
## Lag 0      1.000000000           1.000000000            1.00000000
## Lag 1e+05 -0.025560287           0.019179924           -0.01963993
## Lag 2e+05 -0.002606629           0.001631863            0.01164375
## Lag 3e+05 -0.012289035           0.017207930            0.00236245
## Lag 4e+05  0.013203355          -0.010313224           -0.01749572
## Lag 5e+05  0.012393214          -0.014146107            0.02006803
## Chain 5 
##                   edges nodefactor.race..wa.B nodefactor.race..wa.H
## Lag 0      1.0000000000           1.000000000           1.000000000
## Lag 1e+05  0.0009054197          -0.005400592          -0.019376493
## Lag 2e+05 -0.0256854346          -0.011866056          -0.021833522
## Lag 3e+05  0.0050058580          -0.008008414           0.010399116
## Lag 4e+05  0.0274453228          -0.012414612          -0.010899842
## Lag 5e+05  0.0025467303           0.005753679          -0.006187236
## Chain 6 
##                  edges nodefactor.race..wa.B nodefactor.race..wa.H
## Lag 0      1.000000000           1.000000000          1.0000000000
## Lag 1e+05  0.019364377          -0.012750006          0.0110296874
## Lag 2e+05 -0.005764475          -0.027455507          0.0006239673
## Lag 3e+05  0.017347967           0.003393639          0.0132321771
## Lag 4e+05  0.000884350          -0.003054325         -0.0137799476
## Lag 5e+05 -0.022301216           0.015052424          0.0142459134
## Chain 7 
##                  edges nodefactor.race..wa.B nodefactor.race..wa.H
## Lag 0      1.000000000           1.000000000          1.0000000000
## Lag 1e+05  0.016990353          -0.008017949         -0.0009086738
## Lag 2e+05 -0.003040907           0.024137173          0.0088298218
## Lag 3e+05 -0.006717174           0.007567443         -0.0023874087
## Lag 4e+05  0.025791851          -0.021078755         -0.0010915776
## Lag 5e+05 -0.009758205           0.014931933         -0.0059506438
## Chain 8 
##                  edges nodefactor.race..wa.B nodefactor.race..wa.H
## Lag 0      1.000000000           1.000000000           1.000000000
## Lag 1e+05  0.003702920          -0.005928410          -0.027147198
## Lag 2e+05  0.018761786          -0.004274763          -0.015198987
## Lag 3e+05 -0.007136121           0.003303904          -0.015079505
## Lag 4e+05 -0.016247065          -0.003356730          -0.024898982
## Lag 5e+05  0.016601059           0.019499094           0.005399776
## 
## Sample statistics burn-in diagnostic (Geweke):
## Chain 8 
## 
## Fraction in 1st window = 0.1
## Fraction in 2nd window = 0.5 
## 
##                 edges nodefactor.race..wa.B nodefactor.race..wa.H 
##               -0.2840                0.7097               -0.7415 
## 
## Individual P-values (lower = worse):
##                 edges nodefactor.race..wa.B nodefactor.race..wa.H 
##             0.7764453             0.4778733             0.4584055 
## Joint P-value (lower = worse):  0.7493245 .
## Chain 8 
## 
## Fraction in 1st window = 0.1
## Fraction in 2nd window = 0.5 
## 
##                 edges nodefactor.race..wa.B nodefactor.race..wa.H 
##               -2.8411               -0.6001               -2.0372 
## 
## Individual P-values (lower = worse):
##                 edges nodefactor.race..wa.B nodefactor.race..wa.H 
##           0.004496186           0.548455431           0.041633559 
## Joint P-value (lower = worse):  0.02990708 .
## Chain 8 
## 
## Fraction in 1st window = 0.1
## Fraction in 2nd window = 0.5 
## 
##                 edges nodefactor.race..wa.B nodefactor.race..wa.H 
##                1.5278                2.6987                0.3133 
## 
## Individual P-values (lower = worse):
##                 edges nodefactor.race..wa.B nodefactor.race..wa.H 
##           0.126564007           0.006961244           0.754027049 
## Joint P-value (lower = worse):  0.02374097 .
## Chain 8 
## 
## Fraction in 1st window = 0.1
## Fraction in 2nd window = 0.5 
## 
##                 edges nodefactor.race..wa.B nodefactor.race..wa.H 
##                0.2893                0.1263                0.8609 
## 
## Individual P-values (lower = worse):
##                 edges nodefactor.race..wa.B nodefactor.race..wa.H 
##             0.7723283             0.8994802             0.3892846 
## Joint P-value (lower = worse):  0.8499357 .
## Chain 8 
## 
## Fraction in 1st window = 0.1
## Fraction in 2nd window = 0.5 
## 
##                 edges nodefactor.race..wa.B nodefactor.race..wa.H 
##                0.6673               -0.3933                1.0758 
## 
## Individual P-values (lower = worse):
##                 edges nodefactor.race..wa.B nodefactor.race..wa.H 
##             0.5045959             0.6940699             0.2820053 
## Joint P-value (lower = worse):  0.7086603 .
## Chain 8 
## 
## Fraction in 1st window = 0.1
## Fraction in 2nd window = 0.5 
## 
##                 edges nodefactor.race..wa.B nodefactor.race..wa.H 
##                0.1434               -0.7948                0.9533 
## 
## Individual P-values (lower = worse):
##                 edges nodefactor.race..wa.B nodefactor.race..wa.H 
##             0.8860027             0.4267398             0.3404347 
## Joint P-value (lower = worse):  0.6423003 .
## Chain 8 
## 
## Fraction in 1st window = 0.1
## Fraction in 2nd window = 0.5 
## 
##                 edges nodefactor.race..wa.B nodefactor.race..wa.H 
##                0.7383                0.1633                0.8393 
## 
## Individual P-values (lower = worse):
##                 edges nodefactor.race..wa.B nodefactor.race..wa.H 
##             0.4603143             0.8702701             0.4012915 
## Joint P-value (lower = worse):  0.8497453 .
## Chain 8 
## 
## Fraction in 1st window = 0.1
## Fraction in 2nd window = 0.5 
## 
##                 edges nodefactor.race..wa.B nodefactor.race..wa.H 
##              -1.28947               0.23874              -0.05555 
## 
## Individual P-values (lower = worse):
##                 edges nodefactor.race..wa.B nodefactor.race..wa.H 
##             0.1972337             0.8113058             0.9557018 
## Joint P-value (lower = worse):  0.3748216 .
## Warning in formals(fun): argument is not a function

## 
## MCMC diagnostics shown here are from the last round of simulation, prior to computation of final parameter estimates. Because the final estimates are refinements of those used for this simulation run, these diagnostics may understate model performance. To directly assess the performance of the final model on in-model statistics, please use the GOF command: gof(ergmFitObject, GOF=~model).

Model 3

## Sample statistics summary:
## 
## Iterations = 1e+06:375900000
## Thinning interval = 1e+05 
## Number of chains = 8 
## Sample size per chain = 3750 
## 
## 1. Empirical mean and standard deviation for each variable,
##    plus standard error of the mean:
## 
##                           Mean     SD Naive SE Time-series SE
## edges                  0.69291 21.878 0.126311       0.128010
## nodefactor.race..wa.B  0.29362  9.047 0.052231       0.052081
## nodefactor.race..wa.H -0.40912 13.346 0.077053       0.076049
## nodematch.race..wa.B   0.02565  1.594 0.009204       0.009212
## nodematch.race..wa.H   0.02298  3.650 0.021074       0.021076
## nodematch.race..wa.O   0.82294 16.908 0.097619       0.097303
## 
## 2. Quantiles for each variable:
## 
##                          2.5%     25%     50%    75%  97.5%
## edges                 -41.159 -14.159  0.8414 14.841 43.841
## nodefactor.race..wa.B -16.591  -5.591  0.4092  6.409 18.409
## nodefactor.race..wa.H -26.174  -9.174 -0.1739  8.826 25.826
## nodematch.race..wa.B   -2.540  -1.540 -0.5399  1.460  3.460
## nodematch.race..wa.H   -6.269  -2.269 -0.2690  2.731  7.731
## nodematch.race..wa.O  -31.880 -10.880  1.1200 12.120 35.120
## 
## 
## Sample statistics cross-correlations:
##                            edges nodefactor.race..wa.B
## edges                 1.00000000           0.386569258
## nodefactor.race..wa.B 0.38656926           1.000000000
## nodefactor.race..wa.H 0.51581135           0.145342125
## nodematch.race..wa.B  0.07995475           0.355558325
## nodematch.race..wa.H  0.16779658           0.007270553
## nodematch.race..wa.O  0.77036083          -0.003145322
##                       nodefactor.race..wa.H nodematch.race..wa.B
## edges                           0.515811349          0.079954750
## nodefactor.race..wa.B           0.145342125          0.355558325
## nodefactor.race..wa.H           1.000000000         -0.001411331
## nodematch.race..wa.B           -0.001411331          1.000000000
## nodematch.race..wa.H            0.554030980          0.004486455
## nodematch.race..wa.O           -0.003541365          0.009798063
##                       nodematch.race..wa.H nodematch.race..wa.O
## edges                          0.167796584          0.770360833
## nodefactor.race..wa.B          0.007270553         -0.003145322
## nodefactor.race..wa.H          0.554030980         -0.003541365
## nodematch.race..wa.B           0.004486455          0.009798063
## nodematch.race..wa.H           1.000000000         -0.006426807
## nodematch.race..wa.O          -0.006426807          1.000000000
## 
## Sample statistics auto-correlation:
## Chain 1 
##                  edges nodefactor.race..wa.B nodefactor.race..wa.H
## Lag 0      1.000000000          1.0000000000          1.0000000000
## Lag 1e+05 -0.022675772          0.0006146616         -0.0083120881
## Lag 2e+05 -0.014077697          0.0154202110         -0.0055351461
## Lag 3e+05 -0.006272102         -0.0171592046         -0.0254126728
## Lag 4e+05 -0.013327612          0.0094650800         -0.0007091522
## Lag 5e+05 -0.024821989          0.0104860126         -0.0148144489
##           nodematch.race..wa.B nodematch.race..wa.H nodematch.race..wa.O
## Lag 0              1.000000000         1.0000000000         1.0000000000
## Lag 1e+05          0.032045465        -0.0151649417        -0.0220772699
## Lag 2e+05          0.002226521        -0.0255652509        -0.0093373496
## Lag 3e+05         -0.014934430         0.0001332612         0.0003144278
## Lag 4e+05         -0.026353775        -0.0044141050        -0.0239276402
## Lag 5e+05          0.007644851        -0.0089063489        -0.0333204834
## Chain 2 
##                  edges nodefactor.race..wa.B nodefactor.race..wa.H
## Lag 0      1.000000000           1.000000000          1.0000000000
## Lag 1e+05  0.029121169          -0.010907475          0.0080886913
## Lag 2e+05  0.005738136          -0.004865801         -0.0003358323
## Lag 3e+05 -0.006147485           0.026129451          0.0052815298
## Lag 4e+05 -0.003800107           0.028194188          0.0305087256
## Lag 5e+05  0.007590824          -0.018798471         -0.0155963611
##           nodematch.race..wa.B nodematch.race..wa.H nodematch.race..wa.O
## Lag 0              1.000000000          1.000000000         1.0000000000
## Lag 1e+05         -0.005809010         -0.003737416         0.0046228204
## Lag 2e+05          0.001707830         -0.005358989         0.0169308866
## Lag 3e+05          0.016406659         -0.021736431         0.0049404980
## Lag 4e+05         -0.006844874          0.010828660        -0.0164817799
## Lag 5e+05         -0.008744926         -0.015683156        -0.0008358697
## Chain 3 
##                  edges nodefactor.race..wa.B nodefactor.race..wa.H
## Lag 0      1.000000000           1.000000000          1.0000000000
## Lag 1e+05  0.008874101          -0.011398018          0.0005693972
## Lag 2e+05 -0.021902032           0.010700622         -0.0284040512
## Lag 3e+05 -0.002643022          -0.013065788          0.0097565780
## Lag 4e+05  0.001771536          -0.004795417          0.0105749138
## Lag 5e+05 -0.004393681           0.008282554          0.0203708763
##           nodematch.race..wa.B nodematch.race..wa.H nodematch.race..wa.O
## Lag 0              1.000000000          1.000000000         1.000000e+00
## Lag 1e+05          0.017856540          0.006004845         1.932043e-02
## Lag 2e+05          0.018154177         -0.003368495        -1.336832e-02
## Lag 3e+05          0.004485060         -0.004835573         1.171974e-02
## Lag 4e+05          0.006893821          0.011537571         2.630285e-05
## Lag 5e+05         -0.002408604          0.015793488        -1.109697e-02
## Chain 4 
##                  edges nodefactor.race..wa.B nodefactor.race..wa.H
## Lag 0      1.000000000           1.000000000           1.000000000
## Lag 1e+05  0.035174112           0.016053051           0.021770878
## Lag 2e+05  0.005500856          -0.006241258          -0.007629545
## Lag 3e+05 -0.011271854           0.008741685          -0.006536236
## Lag 4e+05  0.008628064           0.011392173           0.005035628
## Lag 5e+05  0.011434777           0.005337484          -0.005130564
##           nodematch.race..wa.B nodematch.race..wa.H nodematch.race..wa.O
## Lag 0              1.000000000          1.000000000         1.0000000000
## Lag 1e+05          0.003234300         -0.011933744         0.0284146164
## Lag 2e+05          0.017097113         -0.028046341         0.0006783752
## Lag 3e+05         -0.026186738          0.017362015         0.0090995487
## Lag 4e+05         -0.004638035          0.015549463        -0.0083709478
## Lag 5e+05         -0.015393176         -0.003464642         0.0219351839
## Chain 5 
##                  edges nodefactor.race..wa.B nodefactor.race..wa.H
## Lag 0      1.000000000           1.000000000           1.000000000
## Lag 1e+05  0.001509637           0.004808405          -0.003267671
## Lag 2e+05 -0.001255768          -0.014005328          -0.024023341
## Lag 3e+05  0.019736424          -0.019741308           0.001502842
## Lag 4e+05 -0.025926108           0.005920689          -0.011575218
## Lag 5e+05  0.016661959          -0.007618715           0.009986901
##           nodematch.race..wa.B nodematch.race..wa.H nodematch.race..wa.O
## Lag 0             1.0000000000          1.000000000          1.000000000
## Lag 1e+05        -0.0138354969          0.001738005         -0.003628185
## Lag 2e+05        -0.0004870505          0.005157037         -0.003098918
## Lag 3e+05         0.0009086615          0.002116831          0.027899734
## Lag 4e+05         0.0277904495          0.004993505         -0.009911999
## Lag 5e+05         0.0025864668         -0.007109247          0.011832001
## Chain 6 
##                  edges nodefactor.race..wa.B nodefactor.race..wa.H
## Lag 0      1.000000000           1.000000000            1.00000000
## Lag 1e+05 -0.015206093          -0.023619279           -0.01280746
## Lag 2e+05 -0.017565203           0.022687978            0.01124768
## Lag 3e+05  0.006385590           0.017198537           -0.01137232
## Lag 4e+05 -0.004879522           0.004262916           -0.01146235
## Lag 5e+05  0.009011178          -0.013336363           -0.03271418
##           nodematch.race..wa.B nodematch.race..wa.H nodematch.race..wa.O
## Lag 0              1.000000000         1.0000000000          1.000000000
## Lag 1e+05          0.004963816         0.0004390113         -0.001395031
## Lag 2e+05          0.023874443         0.0192964547         -0.006001586
## Lag 3e+05         -0.002378887        -0.0021653707          0.004827755
## Lag 4e+05          0.017723726        -0.0084445674         -0.007017396
## Lag 5e+05         -0.026981104        -0.0159064201          0.014468773
## Chain 7 
##                  edges nodefactor.race..wa.B nodefactor.race..wa.H
## Lag 0      1.000000000           1.000000000           1.000000000
## Lag 1e+05  0.017099436           0.017554840           0.004419538
## Lag 2e+05 -0.024718330           0.021528028          -0.004303942
## Lag 3e+05  0.002036409          -0.006411881          -0.015281415
## Lag 4e+05 -0.005575458           0.008045303          -0.003828651
## Lag 5e+05 -0.016234236          -0.009945874          -0.006132275
##           nodematch.race..wa.B nodematch.race..wa.H nodematch.race..wa.O
## Lag 0              1.000000000          1.000000000          1.000000000
## Lag 1e+05         -0.027030705          0.021045461          0.007545288
## Lag 2e+05         -0.012084245          0.007378371         -0.021859915
## Lag 3e+05         -0.001087241         -0.014811248          0.009740747
## Lag 4e+05         -0.010298133          0.017533198         -0.018320157
## Lag 5e+05          0.008083214         -0.013399691         -0.020915500
## Chain 8 
##                   edges nodefactor.race..wa.B nodefactor.race..wa.H
## Lag 0      1.0000000000           1.000000000           1.000000000
## Lag 1e+05  0.0030419127          -0.015513148          -0.014068116
## Lag 2e+05 -0.0001922772          -0.025769536          -0.026147045
## Lag 3e+05  0.0294109564           0.013958918          -0.015872966
## Lag 4e+05  0.0064599134          -0.003920452           0.003230989
## Lag 5e+05 -0.0182067593          -0.004678824           0.011809763
##           nodematch.race..wa.B nodematch.race..wa.H nodematch.race..wa.O
## Lag 0             1.0000000000          1.000000000          1.000000000
## Lag 1e+05        -0.0077018271         -0.010501068         -0.001814110
## Lag 2e+05        -0.0139263120         -0.016320287         -0.003825018
## Lag 3e+05        -0.0212615865          0.002717656          0.021652751
## Lag 4e+05        -0.0009990131          0.008444423          0.026129735
## Lag 5e+05        -0.0145885672          0.029492799         -0.010239042
## 
## Sample statistics burn-in diagnostic (Geweke):
## Chain 8 
## 
## Fraction in 1st window = 0.1
## Fraction in 2nd window = 0.5 
## 
##                 edges nodefactor.race..wa.B nodefactor.race..wa.H 
##               0.40691              -1.04381               0.95707 
##  nodematch.race..wa.B  nodematch.race..wa.H  nodematch.race..wa.O 
##              -1.18518              -0.22772              -0.03952 
## 
## Individual P-values (lower = worse):
##                 edges nodefactor.race..wa.B nodefactor.race..wa.H 
##             0.6840749             0.2965734             0.3385307 
##  nodematch.race..wa.B  nodematch.race..wa.H  nodematch.race..wa.O 
##             0.2359481             0.8198654             0.9684730 
## Joint P-value (lower = worse):  0.5839334 .
## Chain 8 
## 
## Fraction in 1st window = 0.1
## Fraction in 2nd window = 0.5 
## 
##                 edges nodefactor.race..wa.B nodefactor.race..wa.H 
##              -0.26809               0.17786              -0.57252 
##  nodematch.race..wa.B  nodematch.race..wa.H  nodematch.race..wa.O 
##              -1.31455              -0.52116              -0.04544 
## 
## Individual P-values (lower = worse):
##                 edges nodefactor.race..wa.B nodefactor.race..wa.H 
##             0.7886295             0.8588299             0.5669687 
##  nodematch.race..wa.B  nodematch.race..wa.H  nodematch.race..wa.O 
##             0.1886603             0.6022565             0.9637589 
## Joint P-value (lower = worse):  0.8112875 .
## Chain 8 
## 
## Fraction in 1st window = 0.1
## Fraction in 2nd window = 0.5 
## 
##                 edges nodefactor.race..wa.B nodefactor.race..wa.H 
##                0.9027                0.1736               -0.4147 
##  nodematch.race..wa.B  nodematch.race..wa.H  nodematch.race..wa.O 
##                1.4932                0.4797                1.3789 
## 
## Individual P-values (lower = worse):
##                 edges nodefactor.race..wa.B nodefactor.race..wa.H 
##             0.3666969             0.8621617             0.6783294 
##  nodematch.race..wa.B  nodematch.race..wa.H  nodematch.race..wa.O 
##             0.1353837             0.6314568             0.1679244 
## Joint P-value (lower = worse):  0.3998128 .
## Chain 8 
## 
## Fraction in 1st window = 0.1
## Fraction in 2nd window = 0.5 
## 
##                 edges nodefactor.race..wa.B nodefactor.race..wa.H 
##               1.76301               0.04821               1.38389 
##  nodematch.race..wa.B  nodematch.race..wa.H  nodematch.race..wa.O 
##              -0.27223               2.00927               1.66440 
## 
## Individual P-values (lower = worse):
##                 edges nodefactor.race..wa.B nodefactor.race..wa.H 
##            0.07789838            0.96155220            0.16639093 
##  nodematch.race..wa.B  nodematch.race..wa.H  nodematch.race..wa.O 
##            0.78544311            0.04450815            0.09603332 
## Joint P-value (lower = worse):  0.3242515 .
## Chain 8 
## 
## Fraction in 1st window = 0.1
## Fraction in 2nd window = 0.5 
## 
##                 edges nodefactor.race..wa.B nodefactor.race..wa.H 
##               -1.6685               -0.1474               -1.6330 
##  nodematch.race..wa.B  nodematch.race..wa.H  nodematch.race..wa.O 
##                2.0298               -1.4886               -0.9866 
## 
## Individual P-values (lower = worse):
##                 edges nodefactor.race..wa.B nodefactor.race..wa.H 
##            0.09521441            0.88282989            0.10246827 
##  nodematch.race..wa.B  nodematch.race..wa.H  nodematch.race..wa.O 
##            0.04237977            0.13659792            0.32383529 
## Joint P-value (lower = worse):  0.1572184 .
## Chain 8 
## 
## Fraction in 1st window = 0.1
## Fraction in 2nd window = 0.5 
## 
##                 edges nodefactor.race..wa.B nodefactor.race..wa.H 
##               -2.5351               -0.7746               -1.2012 
##  nodematch.race..wa.B  nodematch.race..wa.H  nodematch.race..wa.O 
##                0.7424                0.7332               -1.7707 
## 
## Individual P-values (lower = worse):
##                 edges nodefactor.race..wa.B nodefactor.race..wa.H 
##            0.01124122            0.43858239            0.22968342 
##  nodematch.race..wa.B  nodematch.race..wa.H  nodematch.race..wa.O 
##            0.45781676            0.46341156            0.07660621 
## Joint P-value (lower = worse):  0.1112494 .
## Chain 8 
## 
## Fraction in 1st window = 0.1
## Fraction in 2nd window = 0.5 
## 
##                 edges nodefactor.race..wa.B nodefactor.race..wa.H 
##               0.01107              -0.56650               0.13873 
##  nodematch.race..wa.B  nodematch.race..wa.H  nodematch.race..wa.O 
##               1.05242               1.08276               0.44641 
## 
## Individual P-values (lower = worse):
##                 edges nodefactor.race..wa.B nodefactor.race..wa.H 
##             0.9911684             0.5710521             0.8896612 
##  nodematch.race..wa.B  nodematch.race..wa.H  nodematch.race..wa.O 
##             0.2926062             0.2789159             0.6553009 
## Joint P-value (lower = worse):  0.7038813 .
## Chain 8 
## 
## Fraction in 1st window = 0.1
## Fraction in 2nd window = 0.5 
## 
##                 edges nodefactor.race..wa.B nodefactor.race..wa.H 
##               0.11380               0.31600              -0.42556 
##  nodematch.race..wa.B  nodematch.race..wa.H  nodematch.race..wa.O 
##              -0.30663               0.04048               0.07267 
## 
## Individual P-values (lower = worse):
##                 edges nodefactor.race..wa.B nodefactor.race..wa.H 
##             0.9093993             0.7520026             0.6704274 
##  nodematch.race..wa.B  nodematch.race..wa.H  nodematch.race..wa.O 
##             0.7591267             0.9677090             0.9420691 
## Joint P-value (lower = worse):  0.8136421 .
## Warning in formals(fun): argument is not a function

## 
## MCMC diagnostics shown here are from the last round of simulation, prior to computation of final parameter estimates. Because the final estimates are refinements of those used for this simulation run, these diagnostics may understate model performance. To directly assess the performance of the final model on in-model statistics, please use the GOF command: gof(ergmFitObject, GOF=~model).

Model 4

## Sample statistics summary:
## 
## Iterations = 1e+06:375900000
## Thinning interval = 1e+05 
## Number of chains = 8 
## Sample size per chain = 3750 
## 
## 1. Empirical mean and standard deviation for each variable,
##    plus standard error of the mean:
## 
##                                     Mean     SD Naive SE Time-series SE
## edges                            2.46385 21.838  0.12608       0.125042
## nodefactor.deg.main.deg.pers.0.1 1.24993 14.291  0.08251       0.082886
## nodefactor.deg.main.deg.pers.0.2 0.14720  6.107  0.03526       0.035273
## nodefactor.deg.main.deg.pers.1.0 0.15200  6.272  0.03621       0.036196
## nodefactor.deg.main.deg.pers.1.1 0.34030 12.431  0.07177       0.072081
## nodefactor.deg.main.deg.pers.1.2 0.94144 12.978  0.07493       0.075542
## nodefactor.race..wa.B            0.30892  9.007  0.05200       0.051818
## nodefactor.race..wa.H            0.76621 13.272  0.07662       0.077434
## nodematch.race..wa.B             0.03198  1.604  0.00926       0.008985
## nodematch.race..wa.H             0.05965  3.656  0.02111       0.021183
## nodematch.race..wa.O             1.46968 16.994  0.09812       0.098807
## 
## 2. Quantiles for each variable:
## 
##                                     2.5%     25%      50%    75%  97.5%
## edges                            -40.159 -12.159  1.84138 16.841 45.841
## nodefactor.deg.main.deg.pers.0.1 -26.310  -8.310  0.68996 10.690 29.690
## nodefactor.deg.main.deg.pers.0.2 -11.371  -4.371 -0.37103  4.629 12.629
## nodefactor.deg.main.deg.pers.1.0 -12.033  -4.033 -0.03347  3.967 12.967
## nodefactor.deg.main.deg.pers.1.1 -23.538  -8.538  0.46214  8.462 25.462
## nodefactor.deg.main.deg.pers.1.2 -23.388  -8.388  0.61188  9.612 26.612
## nodefactor.race..wa.B            -16.591  -5.591  0.40918  6.409 18.409
## nodefactor.race..wa.H            -24.174  -8.174  0.82608  9.826 27.826
## nodematch.race..wa.B              -2.540  -1.540 -0.53985  1.460  3.460
## nodematch.race..wa.H              -6.269  -2.269 -0.26902  2.731  7.731
## nodematch.race..wa.O             -31.880  -9.880  1.11998 13.120 35.120
## 
## 
## Sample statistics cross-correlations:
##                                       edges
## edges                            1.00000000
## nodefactor.deg.main.deg.pers.0.1 0.55125656
## nodefactor.deg.main.deg.pers.0.2 0.25720137
## nodefactor.deg.main.deg.pers.1.0 0.26898698
## nodefactor.deg.main.deg.pers.1.1 0.50102638
## nodefactor.deg.main.deg.pers.1.2 0.51505485
## nodefactor.race..wa.B            0.38515303
## nodefactor.race..wa.H            0.50830123
## nodematch.race..wa.B             0.07625125
## nodematch.race..wa.H             0.16572928
## nodematch.race..wa.O             0.77214352
##                                  nodefactor.deg.main.deg.pers.0.1
## edges                                                  0.55125656
## nodefactor.deg.main.deg.pers.0.1                       1.00000000
## nodefactor.deg.main.deg.pers.0.2                       0.07549957
## nodefactor.deg.main.deg.pers.1.0                       0.07800802
## nodefactor.deg.main.deg.pers.1.1                       0.14349914
## nodefactor.deg.main.deg.pers.1.2                       0.14051105
## nodefactor.race..wa.B                                  0.23541555
## nodefactor.race..wa.H                                  0.24070504
## nodematch.race..wa.B                                   0.04681900
## nodematch.race..wa.H                                   0.06428990
## nodematch.race..wa.O                                   0.43932145
##                                  nodefactor.deg.main.deg.pers.0.2
## edges                                                  0.25720137
## nodefactor.deg.main.deg.pers.0.1                       0.07549957
## nodefactor.deg.main.deg.pers.0.2                       1.00000000
## nodefactor.deg.main.deg.pers.1.0                       0.02893853
## nodefactor.deg.main.deg.pers.1.1                       0.05697431
## nodefactor.deg.main.deg.pers.1.2                       0.06732021
## nodefactor.race..wa.B                                  0.12357105
## nodefactor.race..wa.H                                  0.12744806
## nodematch.race..wa.B                                   0.02040527
## nodematch.race..wa.H                                   0.04648005
## nodematch.race..wa.O                                   0.19172321
##                                  nodefactor.deg.main.deg.pers.1.0
## edges                                                  0.26898698
## nodefactor.deg.main.deg.pers.0.1                       0.07800802
## nodefactor.deg.main.deg.pers.0.2                       0.02893853
## nodefactor.deg.main.deg.pers.1.0                       1.00000000
## nodefactor.deg.main.deg.pers.1.1                       0.06693272
## nodefactor.deg.main.deg.pers.1.2                       0.06835165
## nodefactor.race..wa.B                                  0.09197375
## nodefactor.race..wa.H                                  0.14801133
## nodematch.race..wa.B                                   0.02254600
## nodematch.race..wa.H                                   0.04012153
## nodematch.race..wa.O                                   0.20340052
##                                  nodefactor.deg.main.deg.pers.1.1
## edges                                                  0.50102638
## nodefactor.deg.main.deg.pers.0.1                       0.14349914
## nodefactor.deg.main.deg.pers.0.2                       0.05697431
## nodefactor.deg.main.deg.pers.1.0                       0.06693272
## nodefactor.deg.main.deg.pers.1.1                       1.00000000
## nodefactor.deg.main.deg.pers.1.2                       0.13139593
## nodefactor.race..wa.B                                  0.16529749
## nodefactor.race..wa.H                                  0.31725426
## nodematch.race..wa.B                                   0.02680594
## nodematch.race..wa.H                                   0.12033565
## nodematch.race..wa.O                                   0.36091677
##                                  nodefactor.deg.main.deg.pers.1.2
## edges                                                  0.51505485
## nodefactor.deg.main.deg.pers.0.1                       0.14051105
## nodefactor.deg.main.deg.pers.0.2                       0.06732021
## nodefactor.deg.main.deg.pers.1.0                       0.06835165
## nodefactor.deg.main.deg.pers.1.1                       0.13139593
## nodefactor.deg.main.deg.pers.1.2                       1.00000000
## nodefactor.race..wa.B                                  0.15385775
## nodefactor.race..wa.H                                  0.30651739
## nodematch.race..wa.B                                   0.01908541
## nodematch.race..wa.H                                   0.11840396
## nodematch.race..wa.O                                   0.38960060
##                                  nodefactor.race..wa.B
## edges                                      0.385153033
## nodefactor.deg.main.deg.pers.0.1           0.235415552
## nodefactor.deg.main.deg.pers.0.2           0.123571054
## nodefactor.deg.main.deg.pers.1.0           0.091973747
## nodefactor.deg.main.deg.pers.1.1           0.165297493
## nodefactor.deg.main.deg.pers.1.2           0.153857753
## nodefactor.race..wa.B                      1.000000000
## nodefactor.race..wa.H                      0.144556548
## nodematch.race..wa.B                       0.364753667
## nodematch.race..wa.H                       0.003960033
## nodematch.race..wa.O                      -0.003493389
##                                  nodefactor.race..wa.H
## edges                                      0.508301228
## nodefactor.deg.main.deg.pers.0.1           0.240705044
## nodefactor.deg.main.deg.pers.0.2           0.127448061
## nodefactor.deg.main.deg.pers.1.0           0.148011335
## nodefactor.deg.main.deg.pers.1.1           0.317254263
## nodefactor.deg.main.deg.pers.1.2           0.306517394
## nodefactor.race..wa.B                      0.144556548
## nodefactor.race..wa.H                      1.000000000
## nodematch.race..wa.B                      -0.002287859
## nodematch.race..wa.H                       0.554879545
## nodematch.race..wa.O                      -0.009496518
##                                  nodematch.race..wa.B nodematch.race..wa.H
## edges                                    0.0762512500         0.1657292753
## nodefactor.deg.main.deg.pers.0.1         0.0468189967         0.0642898974
## nodefactor.deg.main.deg.pers.0.2         0.0204052716         0.0464800533
## nodefactor.deg.main.deg.pers.1.0         0.0225459979         0.0401215274
## nodefactor.deg.main.deg.pers.1.1         0.0268059419         0.1203356479
## nodefactor.deg.main.deg.pers.1.2         0.0190854085         0.1184039632
## nodefactor.race..wa.B                    0.3647536668         0.0039600333
## nodefactor.race..wa.H                   -0.0022878586         0.5548795451
## nodematch.race..wa.B                     1.0000000000         0.0009421418
## nodematch.race..wa.H                     0.0009421418         1.0000000000
## nodematch.race..wa.O                     0.0044648171        -0.0060942181
##                                  nodematch.race..wa.O
## edges                                     0.772143520
## nodefactor.deg.main.deg.pers.0.1          0.439321446
## nodefactor.deg.main.deg.pers.0.2          0.191723211
## nodefactor.deg.main.deg.pers.1.0          0.203400524
## nodefactor.deg.main.deg.pers.1.1          0.360916766
## nodefactor.deg.main.deg.pers.1.2          0.389600605
## nodefactor.race..wa.B                    -0.003493389
## nodefactor.race..wa.H                    -0.009496518
## nodematch.race..wa.B                      0.004464817
## nodematch.race..wa.H                     -0.006094218
## nodematch.race..wa.O                      1.000000000
## 
## Sample statistics auto-correlation:
## Chain 1 
##                  edges nodefactor.deg.main.deg.pers.0.1
## Lag 0      1.000000000                      1.000000000
## Lag 1e+05 -0.009329272                      0.002137759
## Lag 2e+05 -0.016015374                      0.010362244
## Lag 3e+05  0.005878918                     -0.015122796
## Lag 4e+05 -0.021252614                     -0.032391113
## Lag 5e+05 -0.008957245                     -0.007523296
##           nodefactor.deg.main.deg.pers.0.2
## Lag 0                          1.000000000
## Lag 1e+05                      0.039681801
## Lag 2e+05                     -0.006118591
## Lag 3e+05                      0.012459735
## Lag 4e+05                      0.003893667
## Lag 5e+05                     -0.022528391
##           nodefactor.deg.main.deg.pers.1.0
## Lag 0                          1.000000000
## Lag 1e+05                     -0.034991308
## Lag 2e+05                     -0.002040746
## Lag 3e+05                     -0.002617928
## Lag 4e+05                     -0.017763451
## Lag 5e+05                      0.022649614
##           nodefactor.deg.main.deg.pers.1.1
## Lag 0                          1.000000000
## Lag 1e+05                     -0.006045159
## Lag 2e+05                     -0.012702262
## Lag 3e+05                      0.009454976
## Lag 4e+05                     -0.012766890
## Lag 5e+05                     -0.005387883
##           nodefactor.deg.main.deg.pers.1.2 nodefactor.race..wa.B
## Lag 0                          1.000000000           1.000000000
## Lag 1e+05                     -0.008740181           0.010412885
## Lag 2e+05                      0.005238224          -0.010344572
## Lag 3e+05                     -0.024177340          -0.005024137
## Lag 4e+05                     -0.029368597          -0.004591150
## Lag 5e+05                      0.014245884           0.009156012
##           nodefactor.race..wa.H nodematch.race..wa.B nodematch.race..wa.H
## Lag 0               1.000000000          1.000000000         1.0000000000
## Lag 1e+05          -0.014110715         -0.028387101        -0.0025949456
## Lag 2e+05           0.031708991         -0.028422825         0.0113576031
## Lag 3e+05          -0.001721649         -0.009505605        -0.0004958602
## Lag 4e+05          -0.007612822          0.025185434         0.0068489320
## Lag 5e+05          -0.033151355          0.022337050        -0.0222616730
##           nodematch.race..wa.O
## Lag 0              1.000000000
## Lag 1e+05         -0.008705597
## Lag 2e+05         -0.026786019
## Lag 3e+05          0.008738070
## Lag 4e+05         -0.011501663
## Lag 5e+05          0.003558997
## Chain 2 
##                   edges nodefactor.deg.main.deg.pers.0.1
## Lag 0      1.0000000000                      1.000000000
## Lag 1e+05  0.0022029639                      0.005241233
## Lag 2e+05  0.0085818113                      0.010166303
## Lag 3e+05  0.0005313363                     -0.016562740
## Lag 4e+05 -0.0186813029                      0.016233984
## Lag 5e+05 -0.0220210648                     -0.004449174
##           nodefactor.deg.main.deg.pers.0.2
## Lag 0                          1.000000000
## Lag 1e+05                      0.006695351
## Lag 2e+05                     -0.011479548
## Lag 3e+05                     -0.009264648
## Lag 4e+05                      0.009918676
## Lag 5e+05                     -0.012731469
##           nodefactor.deg.main.deg.pers.1.0
## Lag 0                           1.00000000
## Lag 1e+05                       0.01239626
## Lag 2e+05                      -0.01104457
## Lag 3e+05                      -0.02498166
## Lag 4e+05                       0.01981440
## Lag 5e+05                       0.01576917
##           nodefactor.deg.main.deg.pers.1.1
## Lag 0                          1.000000000
## Lag 1e+05                     -0.018392805
## Lag 2e+05                     -0.022060840
## Lag 3e+05                     -0.006122224
## Lag 4e+05                      0.002939004
## Lag 5e+05                     -0.010027984
##           nodefactor.deg.main.deg.pers.1.2 nodefactor.race..wa.B
## Lag 0                          1.000000000           1.000000000
## Lag 1e+05                      0.015469674           0.018826142
## Lag 2e+05                     -0.005279943          -0.013621349
## Lag 3e+05                      0.002691343          -0.005630995
## Lag 4e+05                     -0.005428346          -0.022443196
## Lag 5e+05                     -0.004138908          -0.009769093
##           nodefactor.race..wa.H nodematch.race..wa.B nodematch.race..wa.H
## Lag 0              1.0000000000          1.000000000         1.0000000000
## Lag 1e+05         -0.0048462428          0.012539505         0.0046377740
## Lag 2e+05         -0.0001257225         -0.013582644        -0.0210312283
## Lag 3e+05         -0.0167820153          0.002065609        -0.0007765344
## Lag 4e+05          0.0246049394         -0.004653529         0.0057853266
## Lag 5e+05         -0.0041146704         -0.009164514         0.0056567204
##           nodematch.race..wa.O
## Lag 0             1.0000000000
## Lag 1e+05         0.0186367963
## Lag 2e+05        -0.0004014425
## Lag 3e+05         0.0022420535
## Lag 4e+05        -0.0116791683
## Lag 5e+05        -0.0386654382
## Chain 3 
##                  edges nodefactor.deg.main.deg.pers.0.1
## Lag 0      1.000000000                      1.000000000
## Lag 1e+05  0.009129557                      0.035607342
## Lag 2e+05  0.007910213                     -0.014802132
## Lag 3e+05  0.007010217                      0.009266843
## Lag 4e+05 -0.022995657                     -0.007639349
## Lag 5e+05 -0.010028148                     -0.006232587
##           nodefactor.deg.main.deg.pers.0.2
## Lag 0                           1.00000000
## Lag 1e+05                       0.01835202
## Lag 2e+05                      -0.01100983
## Lag 3e+05                       0.01307359
## Lag 4e+05                       0.00250712
## Lag 5e+05                       0.02272802
##           nodefactor.deg.main.deg.pers.1.0
## Lag 0                          1.000000000
## Lag 1e+05                     -0.006157808
## Lag 2e+05                      0.009006919
## Lag 3e+05                     -0.007174803
## Lag 4e+05                     -0.016985017
## Lag 5e+05                      0.007086260
##           nodefactor.deg.main.deg.pers.1.1
## Lag 0                           1.00000000
## Lag 1e+05                       0.03322234
## Lag 2e+05                      -0.01630473
## Lag 3e+05                      -0.00562777
## Lag 4e+05                       0.01261462
## Lag 5e+05                      -0.01525425
##           nodefactor.deg.main.deg.pers.1.2 nodefactor.race..wa.B
## Lag 0                          1.000000000          1.0000000000
## Lag 1e+05                      0.009590951         -0.0117679756
## Lag 2e+05                      0.013658217         -0.0178627541
## Lag 3e+05                     -0.025477234         -0.0084782023
## Lag 4e+05                     -0.013997303         -0.0172666243
## Lag 5e+05                     -0.007182599          0.0008559235
##           nodefactor.race..wa.H nodematch.race..wa.B nodematch.race..wa.H
## Lag 0               1.000000000          1.000000000           1.00000000
## Lag 1e+05           0.013657180          0.018611194          -0.03837237
## Lag 2e+05           0.004922150          0.010945167           0.03146729
## Lag 3e+05          -0.022409334          0.006010626           0.01148593
## Lag 4e+05           0.018840674          0.019670644           0.01621037
## Lag 5e+05          -0.002313068          0.014046025          -0.01990896
##           nodematch.race..wa.O
## Lag 0              1.000000000
## Lag 1e+05          0.032868609
## Lag 2e+05          0.018403751
## Lag 3e+05          0.016451907
## Lag 4e+05          0.004666243
## Lag 5e+05         -0.005575709
## Chain 4 
##                  edges nodefactor.deg.main.deg.pers.0.1
## Lag 0      1.000000000                      1.000000000
## Lag 1e+05 -0.001059910                      0.016948999
## Lag 2e+05  0.006557898                     -0.004513058
## Lag 3e+05 -0.002281785                     -0.012719002
## Lag 4e+05  0.003115736                      0.031905705
## Lag 5e+05 -0.018541980                     -0.031226396
##           nodefactor.deg.main.deg.pers.0.2
## Lag 0                          1.000000000
## Lag 1e+05                     -0.021731093
## Lag 2e+05                      0.006583539
## Lag 3e+05                     -0.018637990
## Lag 4e+05                      0.017599383
## Lag 5e+05                      0.004565398
##           nodefactor.deg.main.deg.pers.1.0
## Lag 0                          1.000000000
## Lag 1e+05                      0.010532739
## Lag 2e+05                     -0.027853442
## Lag 3e+05                      0.017901550
## Lag 4e+05                     -0.006945901
## Lag 5e+05                      0.018588624
##           nodefactor.deg.main.deg.pers.1.1
## Lag 0                         1.0000000000
## Lag 1e+05                    -0.0005893541
## Lag 2e+05                     0.0023775653
## Lag 3e+05                    -0.0074189049
## Lag 4e+05                     0.0238517378
## Lag 5e+05                    -0.0193555029
##           nodefactor.deg.main.deg.pers.1.2 nodefactor.race..wa.B
## Lag 0                          1.000000000           1.000000000
## Lag 1e+05                      0.012052125          -0.028701239
## Lag 2e+05                      0.015309392           0.004455955
## Lag 3e+05                      0.001226807           0.007910515
## Lag 4e+05                     -0.004367875          -0.008984838
## Lag 5e+05                      0.010980387          -0.022163981
##           nodefactor.race..wa.H nodematch.race..wa.B nodematch.race..wa.H
## Lag 0              1.0000000000          1.000000000          1.000000000
## Lag 1e+05          0.0047042356          0.016529458          0.035246271
## Lag 2e+05          0.0008282387         -0.032158726         -0.009004717
## Lag 3e+05          0.0212793313         -0.013293962         -0.004259893
## Lag 4e+05         -0.0113257903         -0.033639684         -0.011840840
## Lag 5e+05          0.0009826457         -0.008663648         -0.006249456
##           nodematch.race..wa.O
## Lag 0              1.000000000
## Lag 1e+05         -0.015137904
## Lag 2e+05          0.006967033
## Lag 3e+05          0.022628362
## Lag 4e+05          0.034160552
## Lag 5e+05         -0.019943541
## Chain 5 
##                  edges nodefactor.deg.main.deg.pers.0.1
## Lag 0      1.000000000                      1.000000000
## Lag 1e+05 -0.002681930                      0.001219762
## Lag 2e+05  0.004176453                      0.001059139
## Lag 3e+05 -0.007743768                     -0.002967688
## Lag 4e+05 -0.030749010                      0.009512368
## Lag 5e+05  0.008055143                     -0.029762941
##           nodefactor.deg.main.deg.pers.0.2
## Lag 0                          1.000000000
## Lag 1e+05                      0.014086793
## Lag 2e+05                     -0.005470278
## Lag 3e+05                     -0.006043754
## Lag 4e+05                      0.009955788
## Lag 5e+05                     -0.007788749
##           nodefactor.deg.main.deg.pers.1.0
## Lag 0                          1.000000000
## Lag 1e+05                      0.020168149
## Lag 2e+05                     -0.024042963
## Lag 3e+05                      0.014847306
## Lag 4e+05                     -0.004076071
## Lag 5e+05                      0.023915707
##           nodefactor.deg.main.deg.pers.1.1
## Lag 0                          1.000000000
## Lag 1e+05                     -0.020370059
## Lag 2e+05                      0.003563453
## Lag 3e+05                     -0.015229307
## Lag 4e+05                     -0.004424009
## Lag 5e+05                      0.004512811
##           nodefactor.deg.main.deg.pers.1.2 nodefactor.race..wa.B
## Lag 0                         1.0000000000           1.000000000
## Lag 1e+05                     0.0161162600           0.013253168
## Lag 2e+05                     0.0005071354           0.003817778
## Lag 3e+05                    -0.0147045524          -0.007922601
## Lag 4e+05                    -0.0259076565          -0.032505679
## Lag 5e+05                    -0.0020651744          -0.025134211
##           nodefactor.race..wa.H nodematch.race..wa.B nodematch.race..wa.H
## Lag 0              1.0000000000         1.000000e+00          1.000000000
## Lag 1e+05         -0.0062994102         4.181164e-05         -0.022698361
## Lag 2e+05          0.0288258077        -8.607390e-03         -0.002034118
## Lag 3e+05         -0.0129872252        -2.464248e-03          0.015758669
## Lag 4e+05         -0.0034746149        -4.674731e-03         -0.011093162
## Lag 5e+05         -0.0004571073         8.239553e-03          0.025753396
##           nodematch.race..wa.O
## Lag 0              1.000000000
## Lag 1e+05         -0.001589239
## Lag 2e+05         -0.028190999
## Lag 3e+05         -0.001594706
## Lag 4e+05         -0.006910989
## Lag 5e+05          0.002869058
## Chain 6 
##                  edges nodefactor.deg.main.deg.pers.0.1
## Lag 0      1.000000000                      1.000000000
## Lag 1e+05 -0.019202128                     -0.010518337
## Lag 2e+05 -0.010748543                      0.004727266
## Lag 3e+05  0.006726598                     -0.019372844
## Lag 4e+05  0.023702703                      0.010697968
## Lag 5e+05  0.008666694                      0.000717902
##           nodefactor.deg.main.deg.pers.0.2
## Lag 0                         1.0000000000
## Lag 1e+05                     0.0240741855
## Lag 2e+05                    -0.0001780886
## Lag 3e+05                    -0.0390591583
## Lag 4e+05                    -0.0255068434
## Lag 5e+05                    -0.0011909667
##           nodefactor.deg.main.deg.pers.1.0
## Lag 0                          1.000000000
## Lag 1e+05                     -0.007601330
## Lag 2e+05                      0.015019503
## Lag 3e+05                     -0.029712148
## Lag 4e+05                      0.008195374
## Lag 5e+05                      0.028019248
##           nodefactor.deg.main.deg.pers.1.1
## Lag 0                          1.000000000
## Lag 1e+05                      0.002192101
## Lag 2e+05                     -0.003640119
## Lag 3e+05                      0.008070529
## Lag 4e+05                     -0.020580428
## Lag 5e+05                      0.029270326
##           nodefactor.deg.main.deg.pers.1.2 nodefactor.race..wa.B
## Lag 0                         1.000000e+00           1.000000000
## Lag 1e+05                     1.751613e-03          -0.004516838
## Lag 2e+05                     3.340118e-05           0.012130905
## Lag 3e+05                    -1.106008e-02           0.013558533
## Lag 4e+05                    -6.562737e-03           0.034643902
## Lag 5e+05                     1.558904e-02          -0.008444868
##           nodefactor.race..wa.H nodematch.race..wa.B nodematch.race..wa.H
## Lag 0              1.0000000000          1.000000000         1.0000000000
## Lag 1e+05          0.0343995861          0.002498648        -0.0056346453
## Lag 2e+05          0.0011212968         -0.036972817        -0.0300242939
## Lag 3e+05          0.0100553117         -0.007817494        -0.0003767314
## Lag 4e+05          0.0023494822          0.012983063         0.0138080603
## Lag 5e+05         -0.0001803568          0.005759302         0.0011324447
##           nodematch.race..wa.O
## Lag 0              1.000000000
## Lag 1e+05         -0.006067265
## Lag 2e+05          0.001772246
## Lag 3e+05          0.032528048
## Lag 4e+05          0.039883696
## Lag 5e+05          0.019952030
## Chain 7 
##                  edges nodefactor.deg.main.deg.pers.0.1
## Lag 0      1.000000000                      1.000000000
## Lag 1e+05 -0.019176627                     -0.016853970
## Lag 2e+05 -0.049892123                     -0.007839650
## Lag 3e+05  0.013482975                      0.004043043
## Lag 4e+05 -0.001746957                      0.011239921
## Lag 5e+05 -0.004556856                      0.029070290
##           nodefactor.deg.main.deg.pers.0.2
## Lag 0                         1.0000000000
## Lag 1e+05                    -0.0166412738
## Lag 2e+05                    -0.0009281719
## Lag 3e+05                     0.0308636162
## Lag 4e+05                    -0.0063423047
## Lag 5e+05                    -0.0184842649
##           nodefactor.deg.main.deg.pers.1.0
## Lag 0                          1.000000000
## Lag 1e+05                     -0.013050736
## Lag 2e+05                      0.012214318
## Lag 3e+05                      0.002630459
## Lag 4e+05                     -0.004016622
## Lag 5e+05                      0.002912891
##           nodefactor.deg.main.deg.pers.1.1
## Lag 0                         1.0000000000
## Lag 1e+05                    -0.0005597757
## Lag 2e+05                    -0.0143705674
## Lag 3e+05                    -0.0183778318
## Lag 4e+05                     0.0224058168
## Lag 5e+05                     0.0100389468
##           nodefactor.deg.main.deg.pers.1.2 nodefactor.race..wa.B
## Lag 0                          1.000000000          1.0000000000
## Lag 1e+05                     -0.007779326         -0.0018968371
## Lag 2e+05                     -0.017691231          0.0001606169
## Lag 3e+05                      0.026543688          0.0321693101
## Lag 4e+05                      0.016814639         -0.0001544169
## Lag 5e+05                      0.023014557          0.0009104194
##           nodefactor.race..wa.H nodematch.race..wa.B nodematch.race..wa.H
## Lag 0               1.000000000           1.00000000         1.0000000000
## Lag 1e+05           0.029971907          -0.03289824         0.0077645067
## Lag 2e+05          -0.014866760          -0.02517302         0.0025388258
## Lag 3e+05           0.016724942          -0.01012301        -0.0120952643
## Lag 4e+05          -0.003488776          -0.02947419         0.0021204182
## Lag 5e+05           0.005022565          -0.01742612         0.0005713957
##           nodematch.race..wa.O
## Lag 0             1.0000000000
## Lag 1e+05        -0.0309721842
## Lag 2e+05        -0.0229189443
## Lag 3e+05         0.0005440191
## Lag 4e+05        -0.0149232487
## Lag 5e+05        -0.0276149222
## Chain 8 
##                   edges nodefactor.deg.main.deg.pers.0.1
## Lag 0      1.0000000000                      1.000000000
## Lag 1e+05  0.0001821106                      0.017854471
## Lag 2e+05  0.0003816720                     -0.002272151
## Lag 3e+05 -0.0150688647                     -0.019199435
## Lag 4e+05 -0.0137277967                     -0.011376993
## Lag 5e+05 -0.0112865338                      0.003664171
##           nodefactor.deg.main.deg.pers.0.2
## Lag 0                          1.000000000
## Lag 1e+05                      0.007174850
## Lag 2e+05                      0.016351147
## Lag 3e+05                      0.004760386
## Lag 4e+05                      0.009687951
## Lag 5e+05                     -0.024348959
##           nodefactor.deg.main.deg.pers.1.0
## Lag 0                          1.000000000
## Lag 1e+05                      0.030494856
## Lag 2e+05                      0.004119293
## Lag 3e+05                      0.012746356
## Lag 4e+05                     -0.020758894
## Lag 5e+05                     -0.001992571
##           nodefactor.deg.main.deg.pers.1.1
## Lag 0                         1.0000000000
## Lag 1e+05                    -0.0076357997
## Lag 2e+05                     0.0018111783
## Lag 3e+05                    -0.0009793702
## Lag 4e+05                     0.0106553987
## Lag 5e+05                     0.0062087410
##           nodefactor.deg.main.deg.pers.1.2 nodefactor.race..wa.B
## Lag 0                          1.000000000          1.0000000000
## Lag 1e+05                      0.007565794          0.0055736133
## Lag 2e+05                      0.032682004          0.0241057799
## Lag 3e+05                      0.006077291         -0.0002379887
## Lag 4e+05                     -0.018755530          0.0107091524
## Lag 5e+05                     -0.001590387         -0.0033756472
##           nodefactor.race..wa.H nodematch.race..wa.B nodematch.race..wa.H
## Lag 0               1.000000000          1.000000000         1.000000e+00
## Lag 1e+05           0.013732138         -0.001949090        -2.289755e-02
## Lag 2e+05           0.013815660         -0.003587892        -5.304174e-04
## Lag 3e+05          -0.007941399          0.010120051         3.491714e-03
## Lag 4e+05          -0.018837060          0.005044419        -7.468697e-03
## Lag 5e+05          -0.006488616         -0.017870868         2.237923e-05
##           nodematch.race..wa.O
## Lag 0              1.000000000
## Lag 1e+05         -0.001234719
## Lag 2e+05         -0.006421063
## Lag 3e+05         -0.009916610
## Lag 4e+05         -0.025445693
## Lag 5e+05         -0.012808565
## 
## Sample statistics burn-in diagnostic (Geweke):
## Chain 8 
## 
## Fraction in 1st window = 0.1
## Fraction in 2nd window = 0.5 
## 
##                            edges nodefactor.deg.main.deg.pers.0.1 
##                          0.13191                          0.33903 
## nodefactor.deg.main.deg.pers.0.2 nodefactor.deg.main.deg.pers.1.0 
##                         -1.44395                          0.09481 
## nodefactor.deg.main.deg.pers.1.1 nodefactor.deg.main.deg.pers.1.2 
##                         -0.25862                          0.06446 
##            nodefactor.race..wa.B            nodefactor.race..wa.H 
##                         -0.58405                         -0.30400 
##             nodematch.race..wa.B             nodematch.race..wa.H 
##                          0.86978                         -1.46359 
##             nodematch.race..wa.O 
##                          0.43511 
## 
## Individual P-values (lower = worse):
##                            edges nodefactor.deg.main.deg.pers.0.1 
##                        0.8950543                        0.7345882 
## nodefactor.deg.main.deg.pers.0.2 nodefactor.deg.main.deg.pers.1.0 
##                        0.1487533                        0.9244669 
## nodefactor.deg.main.deg.pers.1.1 nodefactor.deg.main.deg.pers.1.2 
##                        0.7959251                        0.9486007 
##            nodefactor.race..wa.B            nodefactor.race..wa.H 
##                        0.5591868                        0.7611279 
##             nodematch.race..wa.B             nodematch.race..wa.H 
##                        0.3844192                        0.1433064 
##             nodematch.race..wa.O 
##                        0.6634839 
## Joint P-value (lower = worse):  0.7817768 .
## Chain 8 
## 
## Fraction in 1st window = 0.1
## Fraction in 2nd window = 0.5 
## 
##                            edges nodefactor.deg.main.deg.pers.0.1 
##                           0.4203                           1.0620 
## nodefactor.deg.main.deg.pers.0.2 nodefactor.deg.main.deg.pers.1.0 
##                          -0.1591                          -0.4670 
## nodefactor.deg.main.deg.pers.1.1 nodefactor.deg.main.deg.pers.1.2 
##                           0.7608                          -1.2450 
##            nodefactor.race..wa.B            nodefactor.race..wa.H 
##                           0.7548                           0.2550 
##             nodematch.race..wa.B             nodematch.race..wa.H 
##                           1.8842                          -1.3447 
##             nodematch.race..wa.O 
##                          -0.5973 
## 
## Individual P-values (lower = worse):
##                            edges nodefactor.deg.main.deg.pers.0.1 
##                        0.6742737                        0.2882410 
## nodefactor.deg.main.deg.pers.0.2 nodefactor.deg.main.deg.pers.1.0 
##                        0.8735534                        0.6405027 
## nodefactor.deg.main.deg.pers.1.1 nodefactor.deg.main.deg.pers.1.2 
##                        0.4467649                        0.2131303 
##            nodefactor.race..wa.B            nodefactor.race..wa.H 
##                        0.4503556                        0.7987616 
##             nodematch.race..wa.B             nodematch.race..wa.H 
##                        0.0595404                        0.1787214 
##             nodematch.race..wa.O 
##                        0.5503019 
## Joint P-value (lower = worse):  0.1436464 .
## Chain 8 
## 
## Fraction in 1st window = 0.1
## Fraction in 2nd window = 0.5 
## 
##                            edges nodefactor.deg.main.deg.pers.0.1 
##                           1.3962                           1.9257 
## nodefactor.deg.main.deg.pers.0.2 nodefactor.deg.main.deg.pers.1.0 
##                          -0.1673                          -0.2921 
## nodefactor.deg.main.deg.pers.1.1 nodefactor.deg.main.deg.pers.1.2 
##                           0.4929                           0.6491 
##            nodefactor.race..wa.B            nodefactor.race..wa.H 
##                          -0.4126                          -0.4135 
##             nodematch.race..wa.B             nodematch.race..wa.H 
##                          -1.7093                          -1.1646 
##             nodematch.race..wa.O 
##                           2.0711 
## 
## Individual P-values (lower = worse):
##                            edges nodefactor.deg.main.deg.pers.0.1 
##                       0.16265619                       0.05413875 
## nodefactor.deg.main.deg.pers.0.2 nodefactor.deg.main.deg.pers.1.0 
##                       0.86710715                       0.77019246 
## nodefactor.deg.main.deg.pers.1.1 nodefactor.deg.main.deg.pers.1.2 
##                       0.62209066                       0.51626486 
##            nodefactor.race..wa.B            nodefactor.race..wa.H 
##                       0.67988354                       0.67924869 
##             nodematch.race..wa.B             nodematch.race..wa.H 
##                       0.08739300                       0.24418030 
##             nodematch.race..wa.O 
##                       0.03835179 
## Joint P-value (lower = worse):  0.3612008 .
## Chain 8 
## 
## Fraction in 1st window = 0.1
## Fraction in 2nd window = 0.5 
## 
##                            edges nodefactor.deg.main.deg.pers.0.1 
##                          -0.4689                           1.0930 
## nodefactor.deg.main.deg.pers.0.2 nodefactor.deg.main.deg.pers.1.0 
##                          -0.1442                           0.3198 
## nodefactor.deg.main.deg.pers.1.1 nodefactor.deg.main.deg.pers.1.2 
##                          -1.5961                          -0.6879 
##            nodefactor.race..wa.B            nodefactor.race..wa.H 
##                          -0.9541                           0.1210 
##             nodematch.race..wa.B             nodematch.race..wa.H 
##                          -0.4174                           0.1171 
##             nodematch.race..wa.O 
##                          -0.3837 
## 
## Individual P-values (lower = worse):
##                            edges nodefactor.deg.main.deg.pers.0.1 
##                        0.6391537                        0.2744022 
## nodefactor.deg.main.deg.pers.0.2 nodefactor.deg.main.deg.pers.1.0 
##                        0.8853123                        0.7491385 
## nodefactor.deg.main.deg.pers.1.1 nodefactor.deg.main.deg.pers.1.2 
##                        0.1104628                        0.4915313 
##            nodefactor.race..wa.B            nodefactor.race..wa.H 
##                        0.3400228                        0.9037162 
##             nodematch.race..wa.B             nodematch.race..wa.H 
##                        0.6763992                        0.9067437 
##             nodematch.race..wa.O 
##                        0.7011666 
## Joint P-value (lower = worse):  0.8455335 .
## Chain 8 
## 
## Fraction in 1st window = 0.1
## Fraction in 2nd window = 0.5 
## 
##                            edges nodefactor.deg.main.deg.pers.0.1 
##                           0.3687                          -1.0531 
## nodefactor.deg.main.deg.pers.0.2 nodefactor.deg.main.deg.pers.1.0 
##                           1.3900                           1.1531 
## nodefactor.deg.main.deg.pers.1.1 nodefactor.deg.main.deg.pers.1.2 
##                          -1.5602                           1.3074 
##            nodefactor.race..wa.B            nodefactor.race..wa.H 
##                          -1.0853                          -0.3408 
##             nodematch.race..wa.B             nodematch.race..wa.H 
##                           0.4831                          -0.5173 
##             nodematch.race..wa.O 
##                           1.0678 
## 
## Individual P-values (lower = worse):
##                            edges nodefactor.deg.main.deg.pers.0.1 
##                        0.7123876                        0.2922734 
## nodefactor.deg.main.deg.pers.0.2 nodefactor.deg.main.deg.pers.1.0 
##                        0.1645181                        0.2488726 
## nodefactor.deg.main.deg.pers.1.1 nodefactor.deg.main.deg.pers.1.2 
##                        0.1187223                        0.1910702 
##            nodefactor.race..wa.B            nodefactor.race..wa.H 
##                        0.2778060                        0.7332409 
##             nodematch.race..wa.B             nodematch.race..wa.H 
##                        0.6290573                        0.6049567 
##             nodematch.race..wa.O 
##                        0.2855977 
## Joint P-value (lower = worse):  0.3449352 .
## Chain 8 
## 
## Fraction in 1st window = 0.1
## Fraction in 2nd window = 0.5 
## 
##                            edges nodefactor.deg.main.deg.pers.0.1 
##                         -0.85090                         -0.92078 
## nodefactor.deg.main.deg.pers.0.2 nodefactor.deg.main.deg.pers.1.0 
##                         -1.43987                         -1.02754 
## nodefactor.deg.main.deg.pers.1.1 nodefactor.deg.main.deg.pers.1.2 
##                         -1.66491                         -0.38922 
##            nodefactor.race..wa.B            nodefactor.race..wa.H 
##                         -0.02584                         -2.01699 
##             nodematch.race..wa.B             nodematch.race..wa.H 
##                          1.74810                         -0.62141 
##             nodematch.race..wa.O 
##                          0.19689 
## 
## Individual P-values (lower = worse):
##                            edges nodefactor.deg.main.deg.pers.0.1 
##                       0.39482256                       0.35716417 
## nodefactor.deg.main.deg.pers.0.2 nodefactor.deg.main.deg.pers.1.0 
##                       0.14990417                       0.30416538 
## nodefactor.deg.main.deg.pers.1.1 nodefactor.deg.main.deg.pers.1.2 
##                       0.09593007                       0.69711230 
##            nodefactor.race..wa.B            nodefactor.race..wa.H 
##                       0.97938614                       0.04369614 
##             nodematch.race..wa.B             nodematch.race..wa.H 
##                       0.08044692                       0.53432872 
##             nodematch.race..wa.O 
##                       0.84391393 
## Joint P-value (lower = worse):  0.4239701 .
## Chain 8 
## 
## Fraction in 1st window = 0.1
## Fraction in 2nd window = 0.5 
## 
##                            edges nodefactor.deg.main.deg.pers.0.1 
##                          -0.1953                           0.7327 
## nodefactor.deg.main.deg.pers.0.2 nodefactor.deg.main.deg.pers.1.0 
##                           0.3112                          -0.9586 
## nodefactor.deg.main.deg.pers.1.1 nodefactor.deg.main.deg.pers.1.2 
##                          -0.9816                          -0.4174 
##            nodefactor.race..wa.B            nodefactor.race..wa.H 
##                           0.2383                          -0.3234 
##             nodematch.race..wa.B             nodematch.race..wa.H 
##                          -0.1429                          -1.6783 
##             nodematch.race..wa.O 
##                          -0.2484 
## 
## Individual P-values (lower = worse):
##                            edges nodefactor.deg.main.deg.pers.0.1 
##                       0.84519306                       0.46376388 
## nodefactor.deg.main.deg.pers.0.2 nodefactor.deg.main.deg.pers.1.0 
##                       0.75563243                       0.33776872 
## nodefactor.deg.main.deg.pers.1.1 nodefactor.deg.main.deg.pers.1.2 
##                       0.32629231                       0.67638907 
##            nodefactor.race..wa.B            nodefactor.race..wa.H 
##                       0.81163310                       0.74639660 
##             nodematch.race..wa.B             nodematch.race..wa.H 
##                       0.88638209                       0.09328757 
##             nodematch.race..wa.O 
##                       0.80382615 
## Joint P-value (lower = worse):  0.8176736 .
## Chain 8 
## 
## Fraction in 1st window = 0.1
## Fraction in 2nd window = 0.5 
## 
##                            edges nodefactor.deg.main.deg.pers.0.1 
##                         -1.03716                         -1.69863 
## nodefactor.deg.main.deg.pers.0.2 nodefactor.deg.main.deg.pers.1.0 
##                         -0.93980                         -1.61569 
## nodefactor.deg.main.deg.pers.1.1 nodefactor.deg.main.deg.pers.1.2 
##                         -0.03289                         -0.40026 
##            nodefactor.race..wa.B            nodefactor.race..wa.H 
##                         -1.42270                         -0.55094 
##             nodematch.race..wa.B             nodematch.race..wa.H 
##                          0.82566                          0.40076 
##             nodematch.race..wa.O 
##                         -0.26801 
## 
## Individual P-values (lower = worse):
##                            edges nodefactor.deg.main.deg.pers.0.1 
##                       0.29966048                       0.08938892 
## nodefactor.deg.main.deg.pers.0.2 nodefactor.deg.main.deg.pers.1.0 
##                       0.34732006                       0.10616215 
## nodefactor.deg.main.deg.pers.1.1 nodefactor.deg.main.deg.pers.1.2 
##                       0.97376046                       0.68896709 
##            nodefactor.race..wa.B            nodefactor.race..wa.H 
##                       0.15482325                       0.58167301 
##             nodematch.race..wa.B             nodematch.race..wa.H 
##                       0.40899953                       0.68859354 
##             nodematch.race..wa.O 
##                       0.78869331 
## Joint P-value (lower = worse):  0.6080186 .
## Warning in formals(fun): argument is not a function

## 
## MCMC diagnostics shown here are from the last round of simulation, prior to computation of final parameter estimates. Because the final estimates are refinements of those used for this simulation run, these diagnostics may understate model performance. To directly assess the performance of the final model on in-model statistics, please use the GOF command: gof(ergmFitObject, GOF=~model).

Model 5

## Sample statistics summary:
## 
## Iterations = 1e+06:375900000
## Thinning interval = 1e+05 
## Number of chains = 8 
## Sample size per chain = 3750 
## 
## 1. Empirical mean and standard deviation for each variable,
##    plus standard error of the mean:
## 
##                                      Mean     SD Naive SE Time-series SE
## edges                             1.62348 22.014 0.127097        0.12838
## nodefactor.deg.main.deg.pers.0.1  0.20089 14.299 0.082557        0.08256
## nodefactor.deg.main.deg.pers.0.2  0.75577  6.193 0.035758        0.03575
## nodefactor.deg.main.deg.pers.1.0 -0.06287  6.311 0.036434        0.03667
## nodefactor.deg.main.deg.pers.1.1  0.84267 12.512 0.072237        0.07284
## nodefactor.deg.main.deg.pers.1.2  0.14948 12.971 0.074890        0.07508
## nodefactor.race..wa.B             0.23525  8.941 0.051623        0.05131
## nodefactor.race..wa.H             0.68355 13.378 0.077236        0.07738
## nodefactor.region.EW              0.26292  9.529 0.055015        0.05504
## nodefactor.region.OW              0.70819 17.530 0.101212        0.10159
## nodematch.race..wa.B              0.07225  1.605 0.009269        0.00921
## nodematch.race..wa.H              0.02098  3.694 0.021325        0.02140
## nodematch.race..wa.O              0.85761 17.028 0.098313        0.09764
## 
## 2. Quantiles for each variable:
## 
##                                     2.5%     25%      50%    75%  97.5%
## edges                            -41.159 -13.159  0.84138 16.841 45.841
## nodefactor.deg.main.deg.pers.0.1 -27.310  -9.310 -0.31004  9.690 28.690
## nodefactor.deg.main.deg.pers.0.2 -10.371  -3.371  0.62897  4.629 13.629
## nodefactor.deg.main.deg.pers.1.0 -12.033  -4.033 -0.03347  3.967 12.967
## nodefactor.deg.main.deg.pers.1.1 -22.538  -7.538  0.46214  9.462 25.462
## nodefactor.deg.main.deg.pers.1.2 -24.388  -8.388 -0.38812  8.612 26.612
## nodefactor.race..wa.B            -16.591  -5.591  0.40918  6.409 18.409
## nodefactor.race..wa.H            -25.174  -8.174  0.82608  9.826 27.826
## nodefactor.region.EW             -17.501  -6.501  0.49862  6.499 19.499
## nodefactor.region.OW             -33.486 -11.486  0.51379 12.514 35.514
## nodematch.race..wa.B              -2.540  -1.540 -0.53985  1.460  3.460
## nodematch.race..wa.H              -6.269  -2.269 -0.26902  2.731  7.731
## nodematch.race..wa.O             -31.880 -10.880  1.11998 12.120 34.120
## 
## 
## Sample statistics cross-correlations:
##                                       edges
## edges                            1.00000000
## nodefactor.deg.main.deg.pers.0.1 0.54698097
## nodefactor.deg.main.deg.pers.0.2 0.27373047
## nodefactor.deg.main.deg.pers.1.0 0.27653067
## nodefactor.deg.main.deg.pers.1.1 0.50007230
## nodefactor.deg.main.deg.pers.1.2 0.51732819
## nodefactor.race..wa.B            0.39038739
## nodefactor.race..wa.H            0.51445723
## nodefactor.region.EW             0.40590306
## nodefactor.region.OW             0.63235609
## nodematch.race..wa.B             0.07407811
## nodematch.race..wa.H             0.17390639
## nodematch.race..wa.O             0.77325939
##                                  nodefactor.deg.main.deg.pers.0.1
## edges                                                  0.54698097
## nodefactor.deg.main.deg.pers.0.1                       1.00000000
## nodefactor.deg.main.deg.pers.0.2                       0.07315837
## nodefactor.deg.main.deg.pers.1.0                       0.07656466
## nodefactor.deg.main.deg.pers.1.1                       0.13386176
## nodefactor.deg.main.deg.pers.1.2                       0.14276917
## nodefactor.race..wa.B                                  0.24349541
## nodefactor.race..wa.H                                  0.24701797
## nodefactor.region.EW                                   0.20641904
## nodefactor.region.OW                                   0.34857161
## nodematch.race..wa.B                                   0.05706259
## nodematch.race..wa.H                                   0.07065458
## nodematch.race..wa.O                                   0.43167346
##                                  nodefactor.deg.main.deg.pers.0.2
## edges                                                  0.27373047
## nodefactor.deg.main.deg.pers.0.1                       0.07315837
## nodefactor.deg.main.deg.pers.0.2                       1.00000000
## nodefactor.deg.main.deg.pers.1.0                       0.03535950
## nodefactor.deg.main.deg.pers.1.1                       0.06461245
## nodefactor.deg.main.deg.pers.1.2                       0.07731024
## nodefactor.race..wa.B                                  0.12005774
## nodefactor.race..wa.H                                  0.13659726
## nodefactor.region.EW                                   0.10475302
## nodefactor.region.OW                                   0.18310732
## nodematch.race..wa.B                                   0.03313109
## nodematch.race..wa.H                                   0.03717945
## nodematch.race..wa.O                                   0.20698197
##                                  nodefactor.deg.main.deg.pers.1.0
## edges                                                 0.276530672
## nodefactor.deg.main.deg.pers.0.1                      0.076564660
## nodefactor.deg.main.deg.pers.0.2                      0.035359503
## nodefactor.deg.main.deg.pers.1.0                      1.000000000
## nodefactor.deg.main.deg.pers.1.1                      0.070743960
## nodefactor.deg.main.deg.pers.1.2                      0.071381852
## nodefactor.race..wa.B                                 0.098729992
## nodefactor.race..wa.H                                 0.155421516
## nodefactor.region.EW                                  0.117599309
## nodefactor.region.OW                                  0.175263120
## nodematch.race..wa.B                                  0.008465332
## nodematch.race..wa.H                                  0.054725791
## nodematch.race..wa.O                                  0.208391555
##                                  nodefactor.deg.main.deg.pers.1.1
## edges                                                  0.50007230
## nodefactor.deg.main.deg.pers.0.1                       0.13386176
## nodefactor.deg.main.deg.pers.0.2                       0.06461245
## nodefactor.deg.main.deg.pers.1.0                       0.07074396
## nodefactor.deg.main.deg.pers.1.1                       1.00000000
## nodefactor.deg.main.deg.pers.1.2                       0.13239612
## nodefactor.race..wa.B                                  0.16660200
## nodefactor.race..wa.H                                  0.30745794
## nodefactor.region.EW                                   0.21202121
## nodefactor.region.OW                                   0.32042640
## nodematch.race..wa.B                                   0.01899502
## nodematch.race..wa.H                                   0.12267369
## nodematch.race..wa.O                                   0.37080725
##                                  nodefactor.deg.main.deg.pers.1.2
## edges                                                  0.51732819
## nodefactor.deg.main.deg.pers.0.1                       0.14276917
## nodefactor.deg.main.deg.pers.0.2                       0.07731024
## nodefactor.deg.main.deg.pers.1.0                       0.07138185
## nodefactor.deg.main.deg.pers.1.1                       0.13239612
## nodefactor.deg.main.deg.pers.1.2                       1.00000000
## nodefactor.race..wa.B                                  0.16689152
## nodefactor.race..wa.H                                  0.31698354
## nodefactor.region.EW                                   0.21581508
## nodefactor.region.OW                                   0.31412841
## nodematch.race..wa.B                                   0.03027283
## nodematch.race..wa.H                                   0.12310470
## nodematch.race..wa.O                                   0.38501227
##                                  nodefactor.race..wa.B
## edges                                      0.390387395
## nodefactor.deg.main.deg.pers.0.1           0.243495410
## nodefactor.deg.main.deg.pers.0.2           0.120057737
## nodefactor.deg.main.deg.pers.1.0           0.098729992
## nodefactor.deg.main.deg.pers.1.1           0.166602002
## nodefactor.deg.main.deg.pers.1.2           0.166891522
## nodefactor.race..wa.B                      1.000000000
## nodefactor.race..wa.H                      0.149520973
## nodefactor.region.EW                       0.108743875
## nodefactor.region.OW                       0.217949245
## nodematch.race..wa.B                       0.347929726
## nodematch.race..wa.H                       0.010583217
## nodematch.race..wa.O                       0.004615852
##                                  nodefactor.race..wa.H
## edges                                      0.514457226
## nodefactor.deg.main.deg.pers.0.1           0.247017968
## nodefactor.deg.main.deg.pers.0.2           0.136597261
## nodefactor.deg.main.deg.pers.1.0           0.155421516
## nodefactor.deg.main.deg.pers.1.1           0.307457943
## nodefactor.deg.main.deg.pers.1.2           0.316983543
## nodefactor.race..wa.B                      0.149520973
## nodefactor.race..wa.H                      1.000000000
## nodefactor.region.EW                       0.316311241
## nodefactor.region.OW                       0.297628014
## nodematch.race..wa.B                      -0.008599605
## nodematch.race..wa.H                       0.557221297
## nodematch.race..wa.O                      -0.003301540
##                                  nodefactor.region.EW nodefactor.region.OW
## edges                                     0.405903058           0.63235609
## nodefactor.deg.main.deg.pers.0.1          0.206419044           0.34857161
## nodefactor.deg.main.deg.pers.0.2          0.104753018           0.18310732
## nodefactor.deg.main.deg.pers.1.0          0.117599309           0.17526312
## nodefactor.deg.main.deg.pers.1.1          0.212021213           0.32042640
## nodefactor.deg.main.deg.pers.1.2          0.215815084           0.31412841
## nodefactor.race..wa.B                     0.108743875           0.21794925
## nodefactor.race..wa.H                     0.316311241           0.29762801
## nodefactor.region.EW                      1.000000000           0.12657911
## nodefactor.region.OW                      0.126579115           1.00000000
## nodematch.race..wa.B                      0.006234486           0.03143011
## nodematch.race..wa.H                      0.144255738           0.09257487
## nodematch.race..wa.O                      0.272290280           0.51537745
##                                  nodematch.race..wa.B nodematch.race..wa.H
## edges                                     0.074078110          0.173906393
## nodefactor.deg.main.deg.pers.0.1          0.057062592          0.070654584
## nodefactor.deg.main.deg.pers.0.2          0.033131088          0.037179445
## nodefactor.deg.main.deg.pers.1.0          0.008465332          0.054725791
## nodefactor.deg.main.deg.pers.1.1          0.018995021          0.122673693
## nodefactor.deg.main.deg.pers.1.2          0.030272830          0.123104699
## nodefactor.race..wa.B                     0.347929726          0.010583217
## nodefactor.race..wa.H                    -0.008599605          0.557221297
## nodefactor.region.EW                      0.006234486          0.144255738
## nodefactor.region.OW                      0.031430111          0.092574873
## nodematch.race..wa.B                      1.000000000         -0.004431205
## nodematch.race..wa.H                     -0.004431205          1.000000000
## nodematch.race..wa.O                      0.009287558         -0.001295523
##                                  nodematch.race..wa.O
## edges                                     0.773259394
## nodefactor.deg.main.deg.pers.0.1          0.431673455
## nodefactor.deg.main.deg.pers.0.2          0.206981974
## nodefactor.deg.main.deg.pers.1.0          0.208391555
## nodefactor.deg.main.deg.pers.1.1          0.370807248
## nodefactor.deg.main.deg.pers.1.2          0.385012267
## nodefactor.race..wa.B                     0.004615852
## nodefactor.race..wa.H                    -0.003301540
## nodefactor.region.EW                      0.272290280
## nodefactor.region.OW                      0.515377450
## nodematch.race..wa.B                      0.009287558
## nodematch.race..wa.H                     -0.001295523
## nodematch.race..wa.O                      1.000000000
## 
## Sample statistics auto-correlation:
## Chain 1 
##                  edges nodefactor.deg.main.deg.pers.0.1
## Lag 0      1.000000000                     1.000000e+00
## Lag 1e+05  0.016187796                    -6.080791e-06
## Lag 2e+05  0.035889104                     2.539743e-02
## Lag 3e+05 -0.004815608                     2.638197e-03
## Lag 4e+05  0.013940186                     1.047890e-02
## Lag 5e+05  0.014555359                    -1.047504e-02
##           nodefactor.deg.main.deg.pers.0.2
## Lag 0                          1.000000000
## Lag 1e+05                     -0.026983914
## Lag 2e+05                      0.031497027
## Lag 3e+05                     -0.001314500
## Lag 4e+05                      0.005395386
## Lag 5e+05                     -0.001492040
##           nodefactor.deg.main.deg.pers.1.0
## Lag 0                          1.000000000
## Lag 1e+05                      0.020309811
## Lag 2e+05                      0.014430842
## Lag 3e+05                      0.007767718
## Lag 4e+05                      0.013677005
## Lag 5e+05                     -0.013002634
##           nodefactor.deg.main.deg.pers.1.1
## Lag 0                          1.000000000
## Lag 1e+05                      0.039411835
## Lag 2e+05                      0.049264453
## Lag 3e+05                     -0.002273479
## Lag 4e+05                     -0.016241724
## Lag 5e+05                     -0.011245850
##           nodefactor.deg.main.deg.pers.1.2 nodefactor.race..wa.B
## Lag 0                          1.000000000          1.0000000000
## Lag 1e+05                      0.002897701          0.0158022256
## Lag 2e+05                      0.042136143         -0.0187874230
## Lag 3e+05                     -0.025349143          0.0046895835
## Lag 4e+05                     -0.010519368         -0.0214814123
## Lag 5e+05                     -0.002834213         -0.0004351698
##           nodefactor.race..wa.H nodefactor.region.EW nodefactor.region.OW
## Lag 0               1.000000000           1.00000000         1.0000000000
## Lag 1e+05           0.016197258           0.01571075        -0.0149817464
## Lag 2e+05           0.021309854           0.03553240         0.0224115463
## Lag 3e+05          -0.004592280           0.01098566        -0.0007759948
## Lag 4e+05           0.002669643          -0.02401224         0.0046237857
## Lag 5e+05           0.022020881          -0.00674200         0.0070924428
##           nodematch.race..wa.B nodematch.race..wa.H nodematch.race..wa.O
## Lag 0              1.000000000           1.00000000          1.000000000
## Lag 1e+05          0.011085245           0.01302072          0.018937889
## Lag 2e+05          0.001170427          -0.00485414          0.017129349
## Lag 3e+05          0.016559854          -0.03524559          0.004044786
## Lag 4e+05         -0.009678258          -0.01029398          0.021489725
## Lag 5e+05         -0.022496170           0.02747241          0.007135001
## Chain 2 
##                  edges nodefactor.deg.main.deg.pers.0.1
## Lag 0      1.000000000                      1.000000000
## Lag 1e+05  0.025808881                      0.014874471
## Lag 2e+05 -0.018672989                     -0.006319465
## Lag 3e+05 -0.012627632                      0.003781696
## Lag 4e+05 -0.007924405                      0.022640347
## Lag 5e+05 -0.002355406                      0.001152860
##           nodefactor.deg.main.deg.pers.0.2
## Lag 0                          1.000000000
## Lag 1e+05                     -0.004484704
## Lag 2e+05                      0.005705293
## Lag 3e+05                      0.005694072
## Lag 4e+05                      0.005859980
## Lag 5e+05                      0.019077508
##           nodefactor.deg.main.deg.pers.1.0
## Lag 0                          1.000000000
## Lag 1e+05                      0.029921933
## Lag 2e+05                     -0.017784703
## Lag 3e+05                      0.013780156
## Lag 4e+05                      0.008561375
## Lag 5e+05                      0.026534941
##           nodefactor.deg.main.deg.pers.1.1
## Lag 0                          1.000000000
## Lag 1e+05                      0.004760250
## Lag 2e+05                     -0.017690671
## Lag 3e+05                     -0.001872405
## Lag 4e+05                      0.031607497
## Lag 5e+05                     -0.021708320
##           nodefactor.deg.main.deg.pers.1.2 nodefactor.race..wa.B
## Lag 0                          1.000000000           1.000000000
## Lag 1e+05                      0.015241024          -0.010468802
## Lag 2e+05                     -0.014795533          -0.002238248
## Lag 3e+05                     -0.013132322           0.004991271
## Lag 4e+05                     -0.002340100           0.013534852
## Lag 5e+05                     -0.003920717           0.015296337
##           nodefactor.race..wa.H nodefactor.region.EW nodefactor.region.OW
## Lag 0               1.000000000          1.000000000          1.000000000
## Lag 1e+05           0.014625937          0.018301845         -0.005909434
## Lag 2e+05           0.025614759         -0.001089658         -0.011271204
## Lag 3e+05           0.033889540         -0.012472880         -0.007964291
## Lag 4e+05          -0.005359342         -0.005070644          0.006041083
## Lag 5e+05          -0.013250215          0.004103074         -0.011576843
##           nodematch.race..wa.B nodematch.race..wa.H nodematch.race..wa.O
## Lag 0              1.000000000          1.000000000          1.000000000
## Lag 1e+05          0.000450558         -0.019260723         -0.007114380
## Lag 2e+05          0.022726222         -0.004509393         -0.015157074
## Lag 3e+05          0.006580707          0.024635554         -0.036194078
## Lag 4e+05          0.016328177         -0.002175387          0.016501711
## Lag 5e+05          0.028591996         -0.003185432          0.004673038
## Chain 3 
##                   edges nodefactor.deg.main.deg.pers.0.1
## Lag 0      1.0000000000                      1.000000000
## Lag 1e+05  0.0084915532                      0.004804579
## Lag 2e+05  0.0005003996                      0.020992385
## Lag 3e+05 -0.0024895965                      0.006386404
## Lag 4e+05  0.0127201769                      0.006978649
## Lag 5e+05 -0.0275298284                     -0.028576743
##           nodefactor.deg.main.deg.pers.0.2
## Lag 0                          1.000000000
## Lag 1e+05                     -0.004500237
## Lag 2e+05                     -0.032045358
## Lag 3e+05                     -0.009579918
## Lag 4e+05                      0.004480320
## Lag 5e+05                      0.017903418
##           nodefactor.deg.main.deg.pers.1.0
## Lag 0                           1.00000000
## Lag 1e+05                      -0.01302048
## Lag 2e+05                       0.04291323
## Lag 3e+05                       0.01291883
## Lag 4e+05                       0.01307447
## Lag 5e+05                       0.01050905
##           nodefactor.deg.main.deg.pers.1.1
## Lag 0                          1.000000000
## Lag 1e+05                     -0.006295635
## Lag 2e+05                      0.016519343
## Lag 3e+05                     -0.012641472
## Lag 4e+05                     -0.015811503
## Lag 5e+05                      0.003499972
##           nodefactor.deg.main.deg.pers.1.2 nodefactor.race..wa.B
## Lag 0                          1.000000000           1.000000000
## Lag 1e+05                     -0.003577572          -0.016691834
## Lag 2e+05                      0.001255261          -0.023192229
## Lag 3e+05                      0.002768212          -0.010670448
## Lag 4e+05                     -0.020039010           0.006324612
## Lag 5e+05                      0.012284444          -0.030427221
##           nodefactor.race..wa.H nodefactor.region.EW nodefactor.region.OW
## Lag 0               1.000000000          1.000000000          1.000000000
## Lag 1e+05           0.004538907          0.013618688         -0.016210929
## Lag 2e+05           0.013299149         -0.003682552         -0.003118138
## Lag 3e+05           0.021698927          0.010947242          0.001433354
## Lag 4e+05          -0.017846619          0.003011765          0.015467071
## Lag 5e+05           0.024550751         -0.024080057         -0.005003325
##           nodematch.race..wa.B nodematch.race..wa.H nodematch.race..wa.O
## Lag 0              1.000000000          1.000000000          1.000000000
## Lag 1e+05          0.014250337         -0.002223484          0.001468003
## Lag 2e+05          0.005338555          0.032950624          0.015375824
## Lag 3e+05         -0.010285393         -0.004282717         -0.018018621
## Lag 4e+05         -0.017786173         -0.009882906          0.027185809
## Lag 5e+05          0.034405241          0.004638316         -0.011803023
## Chain 4 
##                  edges nodefactor.deg.main.deg.pers.0.1
## Lag 0      1.000000000                      1.000000000
## Lag 1e+05 -0.007181045                     -0.008926829
## Lag 2e+05  0.006165675                     -0.002933789
## Lag 3e+05 -0.023244701                     -0.015697014
## Lag 4e+05 -0.020476668                      0.011638486
## Lag 5e+05  0.044900217                      0.006601123
##           nodefactor.deg.main.deg.pers.0.2
## Lag 0                          1.000000000
## Lag 1e+05                      0.013787287
## Lag 2e+05                     -0.001509463
## Lag 3e+05                      0.005680327
## Lag 4e+05                      0.008475170
## Lag 5e+05                     -0.009995165
##           nodefactor.deg.main.deg.pers.1.0
## Lag 0                          1.000000000
## Lag 1e+05                     -0.011150762
## Lag 2e+05                      0.022564669
## Lag 3e+05                     -0.026838713
## Lag 4e+05                      0.009369764
## Lag 5e+05                     -0.013928661
##           nodefactor.deg.main.deg.pers.1.1
## Lag 0                          1.000000000
## Lag 1e+05                      0.022827577
## Lag 2e+05                      0.020383892
## Lag 3e+05                      0.009649934
## Lag 4e+05                     -0.015160127
## Lag 5e+05                      0.009460995
##           nodefactor.deg.main.deg.pers.1.2 nodefactor.race..wa.B
## Lag 0                          1.000000000           1.000000000
## Lag 1e+05                      0.008516214          -0.015273279
## Lag 2e+05                     -0.010654300           0.025182987
## Lag 3e+05                      0.017249631          -0.001743646
## Lag 4e+05                     -0.010454873          -0.002231422
## Lag 5e+05                      0.001629581          -0.006950509
##           nodefactor.race..wa.H nodefactor.region.EW nodefactor.region.OW
## Lag 0               1.000000000          1.000000000          1.000000000
## Lag 1e+05          -0.004891430          0.012167807         -0.008940523
## Lag 2e+05           0.018197499          0.007859965          0.001569574
## Lag 3e+05          -0.007156353         -0.023455037          0.025253604
## Lag 4e+05           0.002475056          0.007218500          0.004705354
## Lag 5e+05           0.023224531          0.015789052          0.008739745
##           nodematch.race..wa.B nodematch.race..wa.H nodematch.race..wa.O
## Lag 0              1.000000000          1.000000000          1.000000000
## Lag 1e+05         -0.012558346          0.003380345         -0.005463362
## Lag 2e+05          0.016821101         -0.028793083          0.018928766
## Lag 3e+05         -0.018032099         -0.014982218         -0.011786398
## Lag 4e+05         -0.004597407          0.001619151         -0.023827183
## Lag 5e+05         -0.011499764         -0.038888554          0.032097054
## Chain 5 
##                  edges nodefactor.deg.main.deg.pers.0.1
## Lag 0      1.000000000                      1.000000000
## Lag 1e+05  0.017726119                      0.009010180
## Lag 2e+05 -0.003951497                      0.005962325
## Lag 3e+05 -0.026814638                     -0.007085802
## Lag 4e+05  0.009079379                     -0.012094440
## Lag 5e+05  0.031726000                      0.017177614
##           nodefactor.deg.main.deg.pers.0.2
## Lag 0                          1.000000000
## Lag 1e+05                      0.009342523
## Lag 2e+05                      0.003125512
## Lag 3e+05                     -0.051444390
## Lag 4e+05                     -0.002926697
## Lag 5e+05                      0.014531902
##           nodefactor.deg.main.deg.pers.1.0
## Lag 0                         1.0000000000
## Lag 1e+05                     0.0291205014
## Lag 2e+05                     0.0057613613
## Lag 3e+05                     0.0027061709
## Lag 4e+05                    -0.0007577756
## Lag 5e+05                     0.0288895120
##           nodefactor.deg.main.deg.pers.1.1
## Lag 0                          1.000000000
## Lag 1e+05                      0.010596463
## Lag 2e+05                     -0.008478730
## Lag 3e+05                      0.000727426
## Lag 4e+05                      0.008629513
## Lag 5e+05                      0.016019013
##           nodefactor.deg.main.deg.pers.1.2 nodefactor.race..wa.B
## Lag 0                          1.000000000           1.000000000
## Lag 1e+05                     -0.016521341           0.015575512
## Lag 2e+05                      0.009592362          -0.040774724
## Lag 3e+05                     -0.012550423          -0.001669356
## Lag 4e+05                      0.024920110          -0.001465227
## Lag 5e+05                      0.009610598           0.033741177
##           nodefactor.race..wa.H nodefactor.region.EW nodefactor.region.OW
## Lag 0               1.000000000          1.000000000          1.000000000
## Lag 1e+05          -0.020440290         -0.012961884          0.028763353
## Lag 2e+05          -0.009118616         -0.036623073          0.008335284
## Lag 3e+05          -0.004680362         -0.018087364         -0.003484183
## Lag 4e+05          -0.012142987          0.027257672         -0.001067927
## Lag 5e+05           0.036799402         -0.008348502          0.004455817
##           nodematch.race..wa.B nodematch.race..wa.H nodematch.race..wa.O
## Lag 0             1.0000000000          1.000000000         1.0000000000
## Lag 1e+05         0.0106207614         -0.029037956         0.0092173230
## Lag 2e+05        -0.0287581360         -0.013123757         0.0059646293
## Lag 3e+05         0.0065841654         -0.001467524        -0.0141496019
## Lag 4e+05        -0.0139472489         -0.011468966         0.0254439753
## Lag 5e+05        -0.0001976772          0.009503273         0.0008242743
## Chain 6 
##                  edges nodefactor.deg.main.deg.pers.0.1
## Lag 0      1.000000000                      1.000000000
## Lag 1e+05 -0.005971222                     -0.011789512
## Lag 2e+05 -0.006798380                      0.008531680
## Lag 3e+05 -0.017116356                     -0.005021223
## Lag 4e+05  0.017698729                      0.034507615
## Lag 5e+05 -0.021020044                     -0.008990807
##           nodefactor.deg.main.deg.pers.0.2
## Lag 0                          1.000000000
## Lag 1e+05                     -0.013668835
## Lag 2e+05                      0.009342533
## Lag 3e+05                     -0.005661909
## Lag 4e+05                     -0.000184554
## Lag 5e+05                      0.002787699
##           nodefactor.deg.main.deg.pers.1.0
## Lag 0                         1.000000e+00
## Lag 1e+05                    -1.328340e-02
## Lag 2e+05                    -2.977274e-02
## Lag 3e+05                     1.113210e-02
## Lag 4e+05                    -2.346306e-02
## Lag 5e+05                    -8.003673e-05
##           nodefactor.deg.main.deg.pers.1.1
## Lag 0                          1.000000000
## Lag 1e+05                     -0.028531931
## Lag 2e+05                     -0.005548763
## Lag 3e+05                      0.006734491
## Lag 4e+05                      0.010003939
## Lag 5e+05                      0.001179411
##           nodefactor.deg.main.deg.pers.1.2 nodefactor.race..wa.B
## Lag 0                          1.000000000           1.000000000
## Lag 1e+05                     -0.020599813          -0.019342355
## Lag 2e+05                      0.018666733          -0.009382535
## Lag 3e+05                     -0.003771718           0.006182426
## Lag 4e+05                      0.007482887          -0.020704786
## Lag 5e+05                     -0.007049267           0.014651864
##           nodefactor.race..wa.H nodefactor.region.EW nodefactor.region.OW
## Lag 0               1.000000000          1.000000000         1.000000e+00
## Lag 1e+05          -0.000758072         -0.012610918        -1.218094e-02
## Lag 2e+05           0.029472570          0.005971863         1.100718e-02
## Lag 3e+05           0.007896493          0.025167791        -1.130805e-02
## Lag 4e+05           0.012749742         -0.019024108        -2.147598e-02
## Lag 5e+05          -0.001601906         -0.008231985         2.160392e-05
##           nodematch.race..wa.B nodematch.race..wa.H nodematch.race..wa.O
## Lag 0              1.000000000          1.000000000         1.0000000000
## Lag 1e+05         -0.027067061         -0.002249415        -0.0013603693
## Lag 2e+05          0.004383052         -0.006356829         0.0006718527
## Lag 3e+05          0.006736349          0.029853690         0.0053508649
## Lag 4e+05         -0.012806912         -0.005222702         0.0171963308
## Lag 5e+05         -0.014591903         -0.031030545        -0.0036755822
## Chain 7 
##                  edges nodefactor.deg.main.deg.pers.0.1
## Lag 0      1.000000000                      1.000000000
## Lag 1e+05 -0.003553832                     -0.010549727
## Lag 2e+05  0.011659077                      0.023768406
## Lag 3e+05  0.002234245                      0.004044059
## Lag 4e+05 -0.008151224                      0.015959145
## Lag 5e+05 -0.010113679                      0.004840702
##           nodefactor.deg.main.deg.pers.0.2
## Lag 0                          1.000000000
## Lag 1e+05                      0.028663873
## Lag 2e+05                      0.002122945
## Lag 3e+05                     -0.004857900
## Lag 4e+05                     -0.003089562
## Lag 5e+05                      0.002389556
##           nodefactor.deg.main.deg.pers.1.0
## Lag 0                          1.000000000
## Lag 1e+05                     -0.007977949
## Lag 2e+05                      0.006041645
## Lag 3e+05                      0.012961738
## Lag 4e+05                     -0.001734431
## Lag 5e+05                     -0.035007421
##           nodefactor.deg.main.deg.pers.1.1
## Lag 0                          1.000000000
## Lag 1e+05                     -0.003826189
## Lag 2e+05                      0.003114630
## Lag 3e+05                      0.012073550
## Lag 4e+05                     -0.017093805
## Lag 5e+05                     -0.035589715
##           nodefactor.deg.main.deg.pers.1.2 nodefactor.race..wa.B
## Lag 0                          1.000000000           1.000000000
## Lag 1e+05                     -0.011168927          -0.009282821
## Lag 2e+05                     -0.020159471           0.011231036
## Lag 3e+05                     -0.012426522           0.008898788
## Lag 4e+05                     -0.009987287          -0.011359528
## Lag 5e+05                     -0.017810783           0.008590669
##           nodefactor.race..wa.H nodefactor.region.EW nodefactor.region.OW
## Lag 0               1.000000000          1.000000000          1.000000000
## Lag 1e+05          -0.010408825         -0.008296128         -0.013465459
## Lag 2e+05           0.017235491          0.021405273         -0.011372905
## Lag 3e+05          -0.004019387          0.008443309         -0.003311734
## Lag 4e+05           0.025667656          0.003171449         -0.001280544
## Lag 5e+05          -0.013764937          0.013931209         -0.006109528
##           nodematch.race..wa.B nodematch.race..wa.H nodematch.race..wa.O
## Lag 0              1.000000000          1.000000000          1.000000000
## Lag 1e+05         -0.025554548         -0.024545388         -0.011615100
## Lag 2e+05          0.007795234          0.019322198          0.011500635
## Lag 3e+05         -0.004262554          0.013800374          0.010936985
## Lag 4e+05         -0.022779731          0.008729107         -0.008638700
## Lag 5e+05          0.007446361          0.011046017         -0.008250481
## Chain 8 
##                  edges nodefactor.deg.main.deg.pers.0.1
## Lag 0      1.000000000                      1.000000000
## Lag 1e+05 -0.005069383                     -0.018044988
## Lag 2e+05 -0.010334212                     -0.010275091
## Lag 3e+05 -0.013650254                      0.016700492
## Lag 4e+05 -0.009865934                     -0.007406708
## Lag 5e+05 -0.005268607                     -0.007708503
##           nodefactor.deg.main.deg.pers.0.2
## Lag 0                         1.0000000000
## Lag 1e+05                     0.0168127237
## Lag 2e+05                     0.0175897498
## Lag 3e+05                    -0.0004593286
## Lag 4e+05                    -0.0065832132
## Lag 5e+05                     0.0110405937
##           nodefactor.deg.main.deg.pers.1.0
## Lag 0                         1.0000000000
## Lag 1e+05                    -0.0002281938
## Lag 2e+05                    -0.0048206282
## Lag 3e+05                     0.0156149835
## Lag 4e+05                    -0.0269303930
## Lag 5e+05                     0.0008078189
##           nodefactor.deg.main.deg.pers.1.1
## Lag 0                          1.000000000
## Lag 1e+05                      0.001805101
## Lag 2e+05                     -0.003778046
## Lag 3e+05                     -0.034483184
## Lag 4e+05                     -0.003721362
## Lag 5e+05                     -0.007868365
##           nodefactor.deg.main.deg.pers.1.2 nodefactor.race..wa.B
## Lag 0                          1.000000000          1.0000000000
## Lag 1e+05                     -0.003169739         -0.0272518996
## Lag 2e+05                     -0.016412202         -0.0110820139
## Lag 3e+05                     -0.010433134         -0.0286281622
## Lag 4e+05                     -0.007904731          0.0006034726
## Lag 5e+05                      0.031314238          0.0029330850
##           nodefactor.race..wa.H nodefactor.region.EW nodefactor.region.OW
## Lag 0               1.000000000          1.000000000          1.000000000
## Lag 1e+05          -0.011217684         -0.005225322          0.017203804
## Lag 2e+05          -0.032853827         -0.005382127          0.005929183
## Lag 3e+05          -0.025722727          0.002433176          0.015754378
## Lag 4e+05           0.011777422          0.009590229         -0.004057207
## Lag 5e+05          -0.003653772         -0.008425894         -0.014015313
##           nodematch.race..wa.B nodematch.race..wa.H nodematch.race..wa.O
## Lag 0              1.000000000          1.000000000         1.0000000000
## Lag 1e+05          0.011570387          0.044408355         0.0119196963
## Lag 2e+05          0.008632663         -0.018391653         0.0004945316
## Lag 3e+05         -0.010860957         -0.004435905         0.0010524887
## Lag 4e+05          0.013476416         -0.001845879        -0.0190603888
## Lag 5e+05         -0.010181414          0.032614440        -0.0126100411
## 
## Sample statistics burn-in diagnostic (Geweke):
## Chain 8 
## 
## Fraction in 1st window = 0.1
## Fraction in 2nd window = 0.5 
## 
##                            edges nodefactor.deg.main.deg.pers.0.1 
##                           1.7843                           1.8917 
## nodefactor.deg.main.deg.pers.0.2 nodefactor.deg.main.deg.pers.1.0 
##                           1.3817                          -1.9596 
## nodefactor.deg.main.deg.pers.1.1 nodefactor.deg.main.deg.pers.1.2 
##                           1.5287                           0.4920 
##            nodefactor.race..wa.B            nodefactor.race..wa.H 
##                           0.9590                           1.0851 
##             nodefactor.region.EW             nodefactor.region.OW 
##                           0.9089                           0.6196 
##             nodematch.race..wa.B             nodematch.race..wa.H 
##                           0.5823                           1.6073 
##             nodematch.race..wa.O 
##                           1.3150 
## 
## Individual P-values (lower = worse):
##                            edges nodefactor.deg.main.deg.pers.0.1 
##                       0.07437570                       0.05853062 
## nodefactor.deg.main.deg.pers.0.2 nodefactor.deg.main.deg.pers.1.0 
##                       0.16705941                       0.05004117 
## nodefactor.deg.main.deg.pers.1.1 nodefactor.deg.main.deg.pers.1.2 
##                       0.12633488                       0.62269077 
##            nodefactor.race..wa.B            nodefactor.race..wa.H 
##                       0.33755750                       0.27788916 
##             nodefactor.region.EW             nodefactor.region.OW 
##                       0.36342741                       0.53551275 
##             nodematch.race..wa.B             nodematch.race..wa.H 
##                       0.56039468                       0.10799513 
##             nodematch.race..wa.O 
##                       0.18851157 
## Joint P-value (lower = worse):  0.504595 .
## Chain 8 
## 
## Fraction in 1st window = 0.1
## Fraction in 2nd window = 0.5 
## 
##                            edges nodefactor.deg.main.deg.pers.0.1 
##                          -0.7010                           0.7674 
## nodefactor.deg.main.deg.pers.0.2 nodefactor.deg.main.deg.pers.1.0 
##                           0.1773                          -1.3263 
## nodefactor.deg.main.deg.pers.1.1 nodefactor.deg.main.deg.pers.1.2 
##                          -0.8840                          -0.5336 
##            nodefactor.race..wa.B            nodefactor.race..wa.H 
##                          -1.3129                          -0.6693 
##             nodefactor.region.EW             nodefactor.region.OW 
##                           0.1500                          -0.5449 
##             nodematch.race..wa.B             nodematch.race..wa.H 
##                          -1.4746                          -0.1918 
##             nodematch.race..wa.O 
##                           0.1399 
## 
## Individual P-values (lower = worse):
##                            edges nodefactor.deg.main.deg.pers.0.1 
##                        0.4832834                        0.4428611 
## nodefactor.deg.main.deg.pers.0.2 nodefactor.deg.main.deg.pers.1.0 
##                        0.8592938                        0.1847543 
## nodefactor.deg.main.deg.pers.1.1 nodefactor.deg.main.deg.pers.1.2 
##                        0.3766750                        0.5936415 
##            nodefactor.race..wa.B            nodefactor.race..wa.H 
##                        0.1892326                        0.5033230 
##             nodefactor.region.EW             nodefactor.region.OW 
##                        0.8807348                        0.5858193 
##             nodematch.race..wa.B             nodematch.race..wa.H 
##                        0.1403098                        0.8479130 
##             nodematch.race..wa.O 
##                        0.8887477 
## Joint P-value (lower = worse):  0.8511137 .
## Chain 8 
## 
## Fraction in 1st window = 0.1
## Fraction in 2nd window = 0.5 
## 
##                            edges nodefactor.deg.main.deg.pers.0.1 
##                         -1.29639                         -2.22675 
## nodefactor.deg.main.deg.pers.0.2 nodefactor.deg.main.deg.pers.1.0 
##                         -0.94649                         -1.99026 
## nodefactor.deg.main.deg.pers.1.1 nodefactor.deg.main.deg.pers.1.2 
##                         -0.08967                         -1.05262 
##            nodefactor.race..wa.B            nodefactor.race..wa.H 
##                          0.20753                         -1.77403 
##             nodefactor.region.EW             nodefactor.region.OW 
##                         -0.35745                         -0.46134 
##             nodematch.race..wa.B             nodematch.race..wa.H 
##                          0.65925                         -0.62521 
##             nodematch.race..wa.O 
##                         -0.77535 
## 
## Individual P-values (lower = worse):
##                            edges nodefactor.deg.main.deg.pers.0.1 
##                       0.19484164                       0.02596429 
## nodefactor.deg.main.deg.pers.0.2 nodefactor.deg.main.deg.pers.1.0 
##                       0.34389654                       0.04656223 
## nodefactor.deg.main.deg.pers.1.1 nodefactor.deg.main.deg.pers.1.2 
##                       0.92854854                       0.29251544 
##            nodefactor.race..wa.B            nodefactor.race..wa.H 
##                       0.83559351                       0.07605791 
##             nodefactor.region.EW             nodefactor.region.OW 
##                       0.72075315                       0.64455820 
##             nodematch.race..wa.B             nodematch.race..wa.H 
##                       0.50973536                       0.53183057 
##             nodematch.race..wa.O 
##                       0.43813220 
## Joint P-value (lower = worse):  0.6429223 .
## Chain 8 
## 
## Fraction in 1st window = 0.1
## Fraction in 2nd window = 0.5 
## 
##                            edges nodefactor.deg.main.deg.pers.0.1 
##                           0.6883                           0.0512 
## nodefactor.deg.main.deg.pers.0.2 nodefactor.deg.main.deg.pers.1.0 
##                          -0.9041                           1.1217 
## nodefactor.deg.main.deg.pers.1.1 nodefactor.deg.main.deg.pers.1.2 
##                          -0.9404                           0.2051 
##            nodefactor.race..wa.B            nodefactor.race..wa.H 
##                           0.1345                          -1.0932 
##             nodefactor.region.EW             nodefactor.region.OW 
##                           0.4168                          -0.6631 
##             nodematch.race..wa.B             nodematch.race..wa.H 
##                          -0.6502                          -0.5754 
##             nodematch.race..wa.O 
##                           1.6280 
## 
## Individual P-values (lower = worse):
##                            edges nodefactor.deg.main.deg.pers.0.1 
##                        0.4912639                        0.9591683 
## nodefactor.deg.main.deg.pers.0.2 nodefactor.deg.main.deg.pers.1.0 
##                        0.3659210                        0.2619718 
## nodefactor.deg.main.deg.pers.1.1 nodefactor.deg.main.deg.pers.1.2 
##                        0.3470367                        0.8374691 
##            nodefactor.race..wa.B            nodefactor.race..wa.H 
##                        0.8930048                        0.2743016 
##             nodefactor.region.EW             nodefactor.region.OW 
##                        0.6768181                        0.5072628 
##             nodematch.race..wa.B             nodematch.race..wa.H 
##                        0.5155822                        0.5650431 
##             nodematch.race..wa.O 
##                        0.1035199 
## Joint P-value (lower = worse):  0.5253492 .
## Chain 8 
## 
## Fraction in 1st window = 0.1
## Fraction in 2nd window = 0.5 
## 
##                            edges nodefactor.deg.main.deg.pers.0.1 
##                         -0.71618                         -0.96895 
## nodefactor.deg.main.deg.pers.0.2 nodefactor.deg.main.deg.pers.1.0 
##                         -0.93651                         -0.32185 
## nodefactor.deg.main.deg.pers.1.1 nodefactor.deg.main.deg.pers.1.2 
##                          1.83682                         -0.04303 
##            nodefactor.race..wa.B            nodefactor.race..wa.H 
##                          0.31781                          1.09640 
##             nodefactor.region.EW             nodefactor.region.OW 
##                         -0.88499                          0.63616 
##             nodematch.race..wa.B             nodematch.race..wa.H 
##                          0.75294                          1.84861 
##             nodematch.race..wa.O 
##                         -1.05642 
## 
## Individual P-values (lower = worse):
##                            edges nodefactor.deg.main.deg.pers.0.1 
##                       0.47387936                       0.33256927 
## nodefactor.deg.main.deg.pers.0.2 nodefactor.deg.main.deg.pers.1.0 
##                       0.34900844                       0.74756330 
## nodefactor.deg.main.deg.pers.1.1 nodefactor.deg.main.deg.pers.1.2 
##                       0.06623691                       0.96567590 
##            nodefactor.race..wa.B            nodefactor.race..wa.H 
##                       0.75063082                       0.27290519 
##             nodefactor.region.EW             nodefactor.region.OW 
##                       0.37616204                       0.52467517 
##             nodematch.race..wa.B             nodematch.race..wa.H 
##                       0.45148823                       0.06451471 
##             nodematch.race..wa.O 
##                       0.29077764 
## Joint P-value (lower = worse):  0.677236 .
## Chain 8 
## 
## Fraction in 1st window = 0.1
## Fraction in 2nd window = 0.5 
## 
##                            edges nodefactor.deg.main.deg.pers.0.1 
##                         0.899187                         1.143623 
## nodefactor.deg.main.deg.pers.0.2 nodefactor.deg.main.deg.pers.1.0 
##                         0.318935                        -0.541440 
## nodefactor.deg.main.deg.pers.1.1 nodefactor.deg.main.deg.pers.1.2 
##                         1.378919                         1.299638 
##            nodefactor.race..wa.B            nodefactor.race..wa.H 
##                        -2.452942                        -0.007241 
##             nodefactor.region.EW             nodefactor.region.OW 
##                         0.577695                         0.832607 
##             nodematch.race..wa.B             nodematch.race..wa.H 
##                        -0.854085                        -0.579388 
##             nodematch.race..wa.O 
##                         1.978759 
## 
## Individual P-values (lower = worse):
##                            edges nodefactor.deg.main.deg.pers.0.1 
##                       0.36855327                       0.25277987 
## nodefactor.deg.main.deg.pers.0.2 nodefactor.deg.main.deg.pers.1.0 
##                       0.74977557                       0.58820456 
## nodefactor.deg.main.deg.pers.1.1 nodefactor.deg.main.deg.pers.1.2 
##                       0.16791963                       0.19372497 
##            nodefactor.race..wa.B            nodefactor.race..wa.H 
##                       0.01416933                       0.99422249 
##             nodefactor.region.EW             nodefactor.region.OW 
##                       0.56347024                       0.40506622 
##             nodematch.race..wa.B             nodematch.race..wa.H 
##                       0.39305806                       0.56232771 
##             nodematch.race..wa.O 
##                       0.04784311 
## Joint P-value (lower = worse):  0.3866231 .
## Chain 8 
## 
## Fraction in 1st window = 0.1
## Fraction in 2nd window = 0.5 
## 
##                            edges nodefactor.deg.main.deg.pers.0.1 
##                         -1.18529                         -0.82258 
## nodefactor.deg.main.deg.pers.0.2 nodefactor.deg.main.deg.pers.1.0 
##                         -1.97523                         -0.25778 
## nodefactor.deg.main.deg.pers.1.1 nodefactor.deg.main.deg.pers.1.2 
##                          0.21842                          0.03591 
##            nodefactor.race..wa.B            nodefactor.race..wa.H 
##                         -2.84105                          0.15812 
##             nodefactor.region.EW             nodefactor.region.OW 
##                         -0.67436                         -1.28251 
##             nodematch.race..wa.B             nodematch.race..wa.H 
##                          1.24653                          1.61562 
##             nodematch.race..wa.O 
##                         -0.17450 
## 
## Individual P-values (lower = worse):
##                            edges nodefactor.deg.main.deg.pers.0.1 
##                      0.235902204                      0.410748106 
## nodefactor.deg.main.deg.pers.0.2 nodefactor.deg.main.deg.pers.1.0 
##                      0.048241718                      0.796577585 
## nodefactor.deg.main.deg.pers.1.1 nodefactor.deg.main.deg.pers.1.2 
##                      0.827102294                      0.971355500 
##            nodefactor.race..wa.B            nodefactor.race..wa.H 
##                      0.004496516                      0.874358872 
##             nodefactor.region.EW             nodefactor.region.OW 
##                      0.500084455                      0.199663178 
##             nodematch.race..wa.B             nodematch.race..wa.H 
##                      0.212568348                      0.106175711 
##             nodematch.race..wa.O 
##                      0.861471922 
## Joint P-value (lower = worse):  0.2190713 .
## Chain 8 
## 
## Fraction in 1st window = 0.1
## Fraction in 2nd window = 0.5 
## 
##                            edges nodefactor.deg.main.deg.pers.0.1 
##                           1.0317                           0.5784 
## nodefactor.deg.main.deg.pers.0.2 nodefactor.deg.main.deg.pers.1.0 
##                           1.3558                           1.1666 
## nodefactor.deg.main.deg.pers.1.1 nodefactor.deg.main.deg.pers.1.2 
##                          -0.1895                           0.8031 
##            nodefactor.race..wa.B            nodefactor.race..wa.H 
##                          -0.4648                          -0.2177 
##             nodefactor.region.EW             nodefactor.region.OW 
##                           0.9695                          -1.0944 
##             nodematch.race..wa.B             nodematch.race..wa.H 
##                           0.8819                          -0.4331 
##             nodematch.race..wa.O 
##                           1.7517 
## 
## Individual P-values (lower = worse):
##                            edges nodefactor.deg.main.deg.pers.0.1 
##                       0.30220597                       0.56301648 
## nodefactor.deg.main.deg.pers.0.2 nodefactor.deg.main.deg.pers.1.0 
##                       0.17517569                       0.24339191 
## nodefactor.deg.main.deg.pers.1.1 nodefactor.deg.main.deg.pers.1.2 
##                       0.84972531                       0.42189191 
##            nodefactor.race..wa.B            nodefactor.race..wa.H 
##                       0.64210965                       0.82769544 
##             nodefactor.region.EW             nodefactor.region.OW 
##                       0.33231490                       0.27378439 
##             nodematch.race..wa.B             nodematch.race..wa.H 
##                       0.37782064                       0.66490695 
##             nodematch.race..wa.O 
##                       0.07982862 
## Joint P-value (lower = worse):  0.7217915 .
## Warning in formals(fun): argument is not a function

## 
## MCMC diagnostics shown here are from the last round of simulation, prior to computation of final parameter estimates. Because the final estimates are refinements of those used for this simulation run, these diagnostics may understate model performance. To directly assess the performance of the final model on in-model statistics, please use the GOF command: gof(ergmFitObject, GOF=~model).

Model 6

## Sample statistics summary:
## 
## Iterations = 1e+06:375900000
## Thinning interval = 1e+05 
## Number of chains = 8 
## Sample size per chain = 3750 
## 
## 1. Empirical mean and standard deviation for each variable,
##    plus standard error of the mean:
## 
##                                       Mean     SD Naive SE Time-series SE
## edges                             1.189713 21.924 0.126581       0.127841
## nodefactor.deg.main.deg.pers.0.1  0.645693 14.437 0.083355       0.083802
## nodefactor.deg.main.deg.pers.0.2 -0.041767  6.139 0.035446       0.035761
## nodefactor.deg.main.deg.pers.1.0  0.270196  6.334 0.036571       0.036368
## nodefactor.deg.main.deg.pers.1.1  0.489669 12.447 0.071863       0.072389
## nodefactor.deg.main.deg.pers.1.2 -0.210424 12.914 0.074558       0.075448
## nodefactor.race..wa.B             0.175551  8.981 0.051852       0.051847
## nodefactor.race..wa.H             0.332147 13.145 0.075895       0.075898
## nodefactor.region.EW              0.035258  9.540 0.055078       0.055250
## nodefactor.region.OW              0.647261 17.470 0.100861       0.100780
## nodematch.race..wa.B              0.009549  1.604 0.009259       0.009178
## nodematch.race..wa.H             -0.037154  3.636 0.020992       0.021066
## nodematch.race..wa.O              0.688310 17.051 0.098446       0.099696
## absdiff.sqrt.age                  0.998502 22.767 0.131446       0.129407
## 
## 2. Quantiles for each variable:
## 
##                                     2.5%     25%      50%    75%  97.5%
## edges                            -41.159 -13.159  0.84138 15.841 44.841
## nodefactor.deg.main.deg.pers.0.1 -27.310  -9.310  0.68996 10.690 29.690
## nodefactor.deg.main.deg.pers.0.2 -11.371  -4.371 -0.37103  3.629 12.629
## nodefactor.deg.main.deg.pers.1.0 -12.033  -4.033 -0.03347  3.967 12.967
## nodefactor.deg.main.deg.pers.1.1 -23.538  -7.538  0.46214  8.462 25.462
## nodefactor.deg.main.deg.pers.1.2 -25.388  -9.388 -0.38812  8.612 25.612
## nodefactor.race..wa.B            -16.591  -5.591  0.40918  6.409 18.409
## nodefactor.race..wa.H            -25.174  -9.174 -0.17392  8.826 26.826
## nodefactor.region.EW             -18.501  -6.501 -0.50138  6.499 19.499
## nodefactor.region.OW             -33.486 -11.486  0.51379 12.514 35.514
## nodematch.race..wa.B              -2.540  -1.540 -0.53985  1.460  3.460
## nodematch.race..wa.H              -6.269  -2.269 -0.26902  2.731  7.731
## nodematch.race..wa.O             -31.880 -10.880  0.11998 12.120 34.120
## absdiff.sqrt.age                 -42.491 -14.528  0.56312 16.160 46.556
## 
## 
## Sample statistics cross-correlations:
##                                       edges
## edges                            1.00000000
## nodefactor.deg.main.deg.pers.0.1 0.55591212
## nodefactor.deg.main.deg.pers.0.2 0.26443810
## nodefactor.deg.main.deg.pers.1.0 0.27345813
## nodefactor.deg.main.deg.pers.1.1 0.49603061
## nodefactor.deg.main.deg.pers.1.2 0.50830955
## nodefactor.race..wa.B            0.38338069
## nodefactor.race..wa.H            0.50800263
## nodefactor.region.EW             0.39562963
## nodefactor.region.OW             0.63415240
## nodematch.race..wa.B             0.07499615
## nodematch.race..wa.H             0.16035207
## nodematch.race..wa.O             0.77849422
## absdiff.sqrt.age                 0.76458382
##                                  nodefactor.deg.main.deg.pers.0.1
## edges                                                  0.55591212
## nodefactor.deg.main.deg.pers.0.1                       1.00000000
## nodefactor.deg.main.deg.pers.0.2                       0.06458471
## nodefactor.deg.main.deg.pers.1.0                       0.07574228
## nodefactor.deg.main.deg.pers.1.1                       0.14151839
## nodefactor.deg.main.deg.pers.1.2                       0.13519402
## nodefactor.race..wa.B                                  0.23244591
## nodefactor.race..wa.H                                  0.24274724
## nodefactor.region.EW                                   0.21062606
## nodefactor.region.OW                                   0.35938522
## nodematch.race..wa.B                                   0.05613736
## nodematch.race..wa.H                                   0.05916797
## nodematch.race..wa.O                                   0.44725962
## absdiff.sqrt.age                                       0.42067332
##                                  nodefactor.deg.main.deg.pers.0.2
## edges                                                  0.26443810
## nodefactor.deg.main.deg.pers.0.1                       0.06458471
## nodefactor.deg.main.deg.pers.0.2                       1.00000000
## nodefactor.deg.main.deg.pers.1.0                       0.02791415
## nodefactor.deg.main.deg.pers.1.1                       0.06020182
## nodefactor.deg.main.deg.pers.1.2                       0.07021680
## nodefactor.race..wa.B                                  0.12182483
## nodefactor.race..wa.H                                  0.12275809
## nodefactor.region.EW                                   0.08936127
## nodefactor.region.OW                                   0.18049539
## nodematch.race..wa.B                                   0.03602835
## nodematch.race..wa.H                                   0.04155517
## nodematch.race..wa.O                                   0.20627708
## absdiff.sqrt.age                                       0.20463286
##                                  nodefactor.deg.main.deg.pers.1.0
## edges                                                  0.27345813
## nodefactor.deg.main.deg.pers.0.1                       0.07574228
## nodefactor.deg.main.deg.pers.0.2                       0.02791415
## nodefactor.deg.main.deg.pers.1.0                       1.00000000
## nodefactor.deg.main.deg.pers.1.1                       0.05876234
## nodefactor.deg.main.deg.pers.1.2                       0.06787868
## nodefactor.race..wa.B                                  0.10402766
## nodefactor.race..wa.H                                  0.15012639
## nodefactor.region.EW                                   0.11598603
## nodefactor.region.OW                                   0.17433451
## nodematch.race..wa.B                                   0.01862807
## nodematch.race..wa.H                                   0.05601726
## nodematch.race..wa.O                                   0.20757918
## absdiff.sqrt.age                                       0.20972047
##                                  nodefactor.deg.main.deg.pers.1.1
## edges                                                  0.49603061
## nodefactor.deg.main.deg.pers.0.1                       0.14151839
## nodefactor.deg.main.deg.pers.0.2                       0.06020182
## nodefactor.deg.main.deg.pers.1.0                       0.05876234
## nodefactor.deg.main.deg.pers.1.1                       1.00000000
## nodefactor.deg.main.deg.pers.1.2                       0.12448677
## nodefactor.race..wa.B                                  0.15804092
## nodefactor.race..wa.H                                  0.30050851
## nodefactor.region.EW                                   0.20430064
## nodefactor.region.OW                                   0.31338347
## nodematch.race..wa.B                                   0.01985172
## nodematch.race..wa.H                                   0.10665281
## nodematch.race..wa.O                                   0.37033710
## absdiff.sqrt.age                                       0.37142781
##                                  nodefactor.deg.main.deg.pers.1.2
## edges                                                  0.50830955
## nodefactor.deg.main.deg.pers.0.1                       0.13519402
## nodefactor.deg.main.deg.pers.0.2                       0.07021680
## nodefactor.deg.main.deg.pers.1.0                       0.06787868
## nodefactor.deg.main.deg.pers.1.1                       0.12448677
## nodefactor.deg.main.deg.pers.1.2                       1.00000000
## nodefactor.race..wa.B                                  0.15912636
## nodefactor.race..wa.H                                  0.30731481
## nodefactor.region.EW                                   0.20898824
## nodefactor.region.OW                                   0.31426151
## nodematch.race..wa.B                                   0.01904716
## nodematch.race..wa.H                                   0.10949766
## nodematch.race..wa.O                                   0.37971808
## absdiff.sqrt.age                                       0.39259709
##                                  nodefactor.race..wa.B
## edges                                      0.383380695
## nodefactor.deg.main.deg.pers.0.1           0.232445908
## nodefactor.deg.main.deg.pers.0.2           0.121824835
## nodefactor.deg.main.deg.pers.1.0           0.104027664
## nodefactor.deg.main.deg.pers.1.1           0.158040916
## nodefactor.deg.main.deg.pers.1.2           0.159126360
## nodefactor.race..wa.B                      1.000000000
## nodefactor.race..wa.H                      0.140438360
## nodefactor.region.EW                       0.112324052
## nodefactor.region.OW                       0.211380859
## nodematch.race..wa.B                       0.357616998
## nodematch.race..wa.H                       0.000698402
## nodematch.race..wa.O                       0.001434573
## absdiff.sqrt.age                           0.303108337
##                                  nodefactor.race..wa.H
## edges                                     5.080026e-01
## nodefactor.deg.main.deg.pers.0.1          2.427472e-01
## nodefactor.deg.main.deg.pers.0.2          1.227581e-01
## nodefactor.deg.main.deg.pers.1.0          1.501264e-01
## nodefactor.deg.main.deg.pers.1.1          3.005085e-01
## nodefactor.deg.main.deg.pers.1.2          3.073148e-01
## nodefactor.race..wa.B                     1.404384e-01
## nodefactor.race..wa.H                     1.000000e+00
## nodefactor.region.EW                      3.028779e-01
## nodefactor.region.OW                      2.977940e-01
## nodematch.race..wa.B                      2.479265e-03
## nodematch.race..wa.H                      5.466943e-01
## nodematch.race..wa.O                     -1.568017e-05
## absdiff.sqrt.age                          3.906968e-01
##                                  nodefactor.region.EW nodefactor.region.OW
## edges                                      0.39562963            0.6341524
## nodefactor.deg.main.deg.pers.0.1           0.21062606            0.3593852
## nodefactor.deg.main.deg.pers.0.2           0.08936127            0.1804954
## nodefactor.deg.main.deg.pers.1.0           0.11598603            0.1743345
## nodefactor.deg.main.deg.pers.1.1           0.20430064            0.3133835
## nodefactor.deg.main.deg.pers.1.2           0.20898824            0.3142615
## nodefactor.race..wa.B                      0.11232405            0.2113809
## nodefactor.race..wa.H                      0.30287788            0.2977940
## nodefactor.region.EW                       1.00000000            0.1280193
## nodefactor.region.OW                       0.12801927            1.0000000
## nodematch.race..wa.B                       0.01363517            0.0401896
## nodematch.race..wa.H                       0.13590600            0.0859614
## nodematch.race..wa.O                       0.26774416            0.5194865
## absdiff.sqrt.age                           0.29960318            0.4863703
##                                  nodematch.race..wa.B nodematch.race..wa.H
## edges                                     0.074996149          0.160352068
## nodefactor.deg.main.deg.pers.0.1          0.056137357          0.059167966
## nodefactor.deg.main.deg.pers.0.2          0.036028348          0.041555174
## nodefactor.deg.main.deg.pers.1.0          0.018628073          0.056017259
## nodefactor.deg.main.deg.pers.1.1          0.019851724          0.106652810
## nodefactor.deg.main.deg.pers.1.2          0.019047156          0.109497662
## nodefactor.race..wa.B                     0.357616998          0.000698402
## nodefactor.race..wa.H                     0.002479265          0.546694257
## nodefactor.region.EW                      0.013635171          0.135905997
## nodefactor.region.OW                      0.040189596          0.085961398
## nodematch.race..wa.B                      1.000000000          0.001499866
## nodematch.race..wa.H                      0.001499866          1.000000000
## nodematch.race..wa.O                     -0.000613464         -0.001970742
## absdiff.sqrt.age                          0.064273987          0.127626854
##                                  nodematch.race..wa.O absdiff.sqrt.age
## edges                                    7.784942e-01       0.76458382
## nodefactor.deg.main.deg.pers.0.1         4.472596e-01       0.42067332
## nodefactor.deg.main.deg.pers.0.2         2.062771e-01       0.20463286
## nodefactor.deg.main.deg.pers.1.0         2.075792e-01       0.20972047
## nodefactor.deg.main.deg.pers.1.1         3.703371e-01       0.37142781
## nodefactor.deg.main.deg.pers.1.2         3.797181e-01       0.39259709
## nodefactor.race..wa.B                    1.434573e-03       0.30310834
## nodefactor.race..wa.H                   -1.568017e-05       0.39069683
## nodefactor.region.EW                     2.677442e-01       0.29960318
## nodefactor.region.OW                     5.194865e-01       0.48637032
## nodematch.race..wa.B                    -6.134640e-04       0.06427399
## nodematch.race..wa.H                    -1.970742e-03       0.12762685
## nodematch.race..wa.O                     1.000000e+00       0.59139290
## absdiff.sqrt.age                         5.913929e-01       1.00000000
## 
## Sample statistics auto-correlation:
## Chain 1 
##                  edges nodefactor.deg.main.deg.pers.0.1
## Lag 0      1.000000000                     1.0000000000
## Lag 1e+05  0.015639428                    -0.0075381489
## Lag 2e+05  0.029739597                     0.0161242635
## Lag 3e+05  0.004437324                     0.0057143155
## Lag 4e+05 -0.007268947                    -0.0008818797
## Lag 5e+05  0.018410690                    -0.0031956244
##           nodefactor.deg.main.deg.pers.0.2
## Lag 0                          1.000000000
## Lag 1e+05                     -0.003088706
## Lag 2e+05                     -0.008028803
## Lag 3e+05                      0.009065282
## Lag 4e+05                     -0.031913568
## Lag 5e+05                      0.009823515
##           nodefactor.deg.main.deg.pers.1.0
## Lag 0                          1.000000000
## Lag 1e+05                     -0.013191464
## Lag 2e+05                     -0.002536912
## Lag 3e+05                     -0.031767337
## Lag 4e+05                     -0.018258020
## Lag 5e+05                      0.019230389
##           nodefactor.deg.main.deg.pers.1.1
## Lag 0                         1.0000000000
## Lag 1e+05                     0.0017759450
## Lag 2e+05                     0.0009240739
## Lag 3e+05                     0.0005815743
## Lag 4e+05                     0.0151026570
## Lag 5e+05                     0.0054802639
##           nodefactor.deg.main.deg.pers.1.2 nodefactor.race..wa.B
## Lag 0                         1.0000000000          1.0000000000
## Lag 1e+05                    -0.0110423959         -0.0219456975
## Lag 2e+05                     0.0006392008         -0.0004201364
## Lag 3e+05                    -0.0121550463         -0.0162648282
## Lag 4e+05                     0.0350538111         -0.0048677581
## Lag 5e+05                     0.0068886534         -0.0007675764
##           nodefactor.race..wa.H nodefactor.region.EW nodefactor.region.OW
## Lag 0              1.0000000000          1.000000000          1.000000000
## Lag 1e+05          0.0138301862          0.013398997         -0.004006493
## Lag 2e+05          0.0007955239          0.020698867          0.004643618
## Lag 3e+05          0.0053702727         -0.011206711          0.014720305
## Lag 4e+05          0.0071200229          0.009793259          0.001856337
## Lag 5e+05          0.0037184999         -0.015013487          0.033970021
##           nodematch.race..wa.B nodematch.race..wa.H nodematch.race..wa.O
## Lag 0              1.000000000          1.000000000          1.000000000
## Lag 1e+05          0.007002546          0.006198415          0.014962849
## Lag 2e+05         -0.006525974         -0.003613460          0.023248283
## Lag 3e+05          0.012655812         -0.016096745         -0.006757479
## Lag 4e+05         -0.002003556         -0.010960502          0.020444929
## Lag 5e+05         -0.017350162          0.020417128          0.020571621
##           absdiff.sqrt.age
## Lag 0          1.000000000
## Lag 1e+05      0.001116059
## Lag 2e+05     -0.007936980
## Lag 3e+05      0.014579869
## Lag 4e+05     -0.018629482
## Lag 5e+05      0.006166657
## Chain 2 
##                   edges nodefactor.deg.main.deg.pers.0.1
## Lag 0      1.0000000000                      1.000000000
## Lag 1e+05 -0.0290309273                     -0.039787119
## Lag 2e+05 -0.0203074970                     -0.011480284
## Lag 3e+05  0.0277578548                      0.025066830
## Lag 4e+05  0.0005155407                      0.000111389
## Lag 5e+05 -0.0221963780                     -0.005350393
##           nodefactor.deg.main.deg.pers.0.2
## Lag 0                           1.00000000
## Lag 1e+05                      -0.02896627
## Lag 2e+05                       0.02796971
## Lag 3e+05                       0.03552105
## Lag 4e+05                      -0.01171522
## Lag 5e+05                       0.01868123
##           nodefactor.deg.main.deg.pers.1.0
## Lag 0                          1.000000000
## Lag 1e+05                      0.033035884
## Lag 2e+05                      0.014034214
## Lag 3e+05                      0.021658058
## Lag 4e+05                     -0.003103217
## Lag 5e+05                      0.014882570
##           nodefactor.deg.main.deg.pers.1.1
## Lag 0                          1.000000000
## Lag 1e+05                      0.036106211
## Lag 2e+05                      0.004209154
## Lag 3e+05                     -0.010850066
## Lag 4e+05                      0.001481208
## Lag 5e+05                     -0.009647078
##           nodefactor.deg.main.deg.pers.1.2 nodefactor.race..wa.B
## Lag 0                          1.000000000           1.000000000
## Lag 1e+05                     -0.007881757          -0.003185169
## Lag 2e+05                      0.012347734          -0.020194874
## Lag 3e+05                      0.017318402          -0.003354750
## Lag 4e+05                     -0.030852391          -0.014823966
## Lag 5e+05                     -0.022482993           0.010357453
##           nodefactor.race..wa.H nodefactor.region.EW nodefactor.region.OW
## Lag 0               1.000000000         1.0000000000           1.00000000
## Lag 1e+05          -0.004344714        -0.0002710276          -0.03659248
## Lag 2e+05          -0.012548328         0.0075237290          -0.01764495
## Lag 3e+05           0.003845897         0.0139026417          -0.01666552
## Lag 4e+05           0.004673396        -0.0073074932          -0.02680332
## Lag 5e+05           0.002696159         0.0025992264           0.01652033
##           nodematch.race..wa.B nodematch.race..wa.H nodematch.race..wa.O
## Lag 0              1.000000000          1.000000000          1.000000000
## Lag 1e+05          0.005022363          0.005925113         -0.034540236
## Lag 2e+05         -0.012735899          0.005718384         -0.003462508
## Lag 3e+05         -0.007674051         -0.008523381          0.025757444
## Lag 4e+05          0.014134855         -0.009746605          0.009347980
## Lag 5e+05          0.014561609          0.009932555         -0.021292046
##           absdiff.sqrt.age
## Lag 0          1.000000000
## Lag 1e+05     -0.033429470
## Lag 2e+05     -0.009695349
## Lag 3e+05      0.007970883
## Lag 4e+05     -0.009644449
## Lag 5e+05      0.009486099
## Chain 3 
##                  edges nodefactor.deg.main.deg.pers.0.1
## Lag 0      1.000000000                     1.0000000000
## Lag 1e+05  0.006895065                    -0.0038768301
## Lag 2e+05  0.011633541                    -0.0172810800
## Lag 3e+05 -0.008307610                    -0.0007647296
## Lag 4e+05  0.011172434                     0.0177191742
## Lag 5e+05 -0.021665982                    -0.0088932741
##           nodefactor.deg.main.deg.pers.0.2
## Lag 0                          1.000000000
## Lag 1e+05                     -0.005009565
## Lag 2e+05                      0.002852452
## Lag 3e+05                      0.001069893
## Lag 4e+05                     -0.006614960
## Lag 5e+05                     -0.007788770
##           nodefactor.deg.main.deg.pers.1.0
## Lag 0                           1.00000000
## Lag 1e+05                      -0.01669872
## Lag 2e+05                      -0.01758410
## Lag 3e+05                       0.01199768
## Lag 4e+05                      -0.02465833
## Lag 5e+05                      -0.00108392
##           nodefactor.deg.main.deg.pers.1.1
## Lag 0                          1.000000000
## Lag 1e+05                     -0.001694849
## Lag 2e+05                     -0.007041408
## Lag 3e+05                     -0.028443219
## Lag 4e+05                      0.009218897
## Lag 5e+05                     -0.049514358
##           nodefactor.deg.main.deg.pers.1.2 nodefactor.race..wa.B
## Lag 0                          1.000000000           1.000000000
## Lag 1e+05                      0.006454705           0.008094175
## Lag 2e+05                      0.014700586          -0.002839267
## Lag 3e+05                     -0.002587302           0.001143273
## Lag 4e+05                     -0.018813435          -0.016308708
## Lag 5e+05                     -0.030574860          -0.008320280
##           nodefactor.race..wa.H nodefactor.region.EW nodefactor.region.OW
## Lag 0               1.000000000         1.0000000000         1.0000000000
## Lag 1e+05          -0.011170516         0.0092333491        -0.0105373843
## Lag 2e+05           0.002729843        -0.0055320000         0.0140708141
## Lag 3e+05           0.017491271        -0.0097960779         0.0008860126
## Lag 4e+05          -0.009595410         0.0349754205         0.0163821508
## Lag 5e+05          -0.017504586        -0.0002574136        -0.0111132231
##           nodematch.race..wa.B nodematch.race..wa.H nodematch.race..wa.O
## Lag 0               1.00000000           1.00000000          1.000000000
## Lag 1e+05           0.01536764           0.02686632         -0.017573164
## Lag 2e+05          -0.01370400           0.01146938         -0.005879545
## Lag 3e+05          -0.01019450           0.02075564         -0.011104557
## Lag 4e+05          -0.01981092           0.02309589          0.026157677
## Lag 5e+05          -0.02556634           0.01268123         -0.000635951
##           absdiff.sqrt.age
## Lag 0          1.000000000
## Lag 1e+05      0.008354287
## Lag 2e+05      0.008883139
## Lag 3e+05     -0.003008616
## Lag 4e+05      0.018826394
## Lag 5e+05     -0.007555189
## Chain 4 
##                   edges nodefactor.deg.main.deg.pers.0.1
## Lag 0      1.0000000000                     1.0000000000
## Lag 1e+05 -0.0001373139                    -0.0187795761
## Lag 2e+05 -0.0328464665                    -0.0186557594
## Lag 3e+05  0.0196746259                     0.0071373997
## Lag 4e+05  0.0300349593                    -0.0007255859
## Lag 5e+05 -0.0066158193                    -0.0030375924
##           nodefactor.deg.main.deg.pers.0.2
## Lag 0                          1.000000000
## Lag 1e+05                      0.003514960
## Lag 2e+05                      0.003992371
## Lag 3e+05                      0.006030236
## Lag 4e+05                      0.028936796
## Lag 5e+05                      0.011158809
##           nodefactor.deg.main.deg.pers.1.0
## Lag 0                         1.0000000000
## Lag 1e+05                    -0.0201131154
## Lag 2e+05                    -0.0051955928
## Lag 3e+05                    -0.0174371766
## Lag 4e+05                     0.0132795103
## Lag 5e+05                    -0.0002295696
##           nodefactor.deg.main.deg.pers.1.1
## Lag 0                         1.0000000000
## Lag 1e+05                     0.0343485545
## Lag 2e+05                     0.0258261286
## Lag 3e+05                     0.0053252010
## Lag 4e+05                    -0.0030384055
## Lag 5e+05                     0.0001929692
##           nodefactor.deg.main.deg.pers.1.2 nodefactor.race..wa.B
## Lag 0                         1.0000000000           1.000000000
## Lag 1e+05                    -0.0048736327          -0.005629042
## Lag 2e+05                    -0.0205322394          -0.019179812
## Lag 3e+05                    -0.0005043537          -0.006951293
## Lag 4e+05                     0.0267432443           0.012913563
## Lag 5e+05                    -0.0091825601           0.007621813
##           nodefactor.race..wa.H nodefactor.region.EW nodefactor.region.OW
## Lag 0               1.000000000         1.0000000000          1.000000000
## Lag 1e+05          -0.019557962         0.0001740286         -0.010092181
## Lag 2e+05          -0.008694067         0.0148882388         -0.010176647
## Lag 3e+05          -0.024683145         0.0002589534          0.027198868
## Lag 4e+05           0.005262817        -0.0216157605          0.011735269
## Lag 5e+05          -0.008770376        -0.0021494300         -0.002400858
##           nodematch.race..wa.B nodematch.race..wa.H nodematch.race..wa.O
## Lag 0             1.0000000000          1.000000000          1.000000000
## Lag 1e+05        -0.0136555561         -0.019490391          0.017059172
## Lag 2e+05        -0.0112070332         -0.006374499         -0.032926032
## Lag 3e+05        -0.0146943340         -0.019519488          0.024855185
## Lag 4e+05        -0.0156432419          0.018666731          0.021738726
## Lag 5e+05        -0.0003011011         -0.004740596          0.007178304
##           absdiff.sqrt.age
## Lag 0          1.000000000
## Lag 1e+05     -0.009508579
## Lag 2e+05      0.004901388
## Lag 3e+05      0.001593036
## Lag 4e+05      0.023898882
## Lag 5e+05     -0.010446095
## Chain 5 
##                  edges nodefactor.deg.main.deg.pers.0.1
## Lag 0      1.000000000                      1.000000000
## Lag 1e+05  0.005604239                      0.024954060
## Lag 2e+05  0.025020051                      0.026463678
## Lag 3e+05  0.014414874                      0.009186940
## Lag 4e+05 -0.015216668                      0.023119384
## Lag 5e+05 -0.004237965                      0.004845083
##           nodefactor.deg.main.deg.pers.0.2
## Lag 0                          1.000000000
## Lag 1e+05                      0.033099346
## Lag 2e+05                     -0.012422938
## Lag 3e+05                      0.014287635
## Lag 4e+05                      0.016379306
## Lag 5e+05                      0.007842349
##           nodefactor.deg.main.deg.pers.1.0
## Lag 0                          1.000000000
## Lag 1e+05                      0.023696298
## Lag 2e+05                     -0.005212683
## Lag 3e+05                      0.012645741
## Lag 4e+05                      0.016135019
## Lag 5e+05                      0.029521874
##           nodefactor.deg.main.deg.pers.1.1
## Lag 0                          1.000000000
## Lag 1e+05                      0.007228309
## Lag 2e+05                      0.012245129
## Lag 3e+05                     -0.030071428
## Lag 4e+05                     -0.016809195
## Lag 5e+05                     -0.025309319
##           nodefactor.deg.main.deg.pers.1.2 nodefactor.race..wa.B
## Lag 0                         1.0000000000           1.000000000
## Lag 1e+05                    -0.0133755881           0.004252881
## Lag 2e+05                    -0.0006316614          -0.018873172
## Lag 3e+05                     0.0124967560           0.025786091
## Lag 4e+05                    -0.0030926443           0.022327601
## Lag 5e+05                    -0.0215794938           0.001026766
##           nodefactor.race..wa.H nodefactor.region.EW nodefactor.region.OW
## Lag 0               1.000000000          1.000000000         1.0000000000
## Lag 1e+05          -0.019031118          0.008349919        -0.0128186540
## Lag 2e+05           0.015778949         -0.009316558         0.0135620561
## Lag 3e+05          -0.013464751         -0.002791012        -0.0009419774
## Lag 4e+05          -0.006800818          0.009304091        -0.0134563052
## Lag 5e+05          -0.014074432          0.023585974         0.0014430338
##           nodematch.race..wa.B nodematch.race..wa.H nodematch.race..wa.O
## Lag 0              1.000000000         1.0000000000         1.0000000000
## Lag 1e+05         -0.046265117         0.0120844601         0.0157247632
## Lag 2e+05          0.003431572        -0.0216573055         0.0326777588
## Lag 3e+05          0.003985561        -0.0021309770         0.0006952747
## Lag 4e+05          0.018422781        -0.0006185005        -0.0057015447
## Lag 5e+05         -0.020206237        -0.0181989141         0.0009979808
##           absdiff.sqrt.age
## Lag 0          1.000000000
## Lag 1e+05      0.006136346
## Lag 2e+05      0.007343563
## Lag 3e+05     -0.009421597
## Lag 4e+05     -0.012758190
## Lag 5e+05     -0.006020123
## Chain 6 
##                  edges nodefactor.deg.main.deg.pers.0.1
## Lag 0      1.000000000                     1.0000000000
## Lag 1e+05  0.037840525                     0.0291431022
## Lag 2e+05 -0.007980122                    -0.0009526951
## Lag 3e+05 -0.002186117                    -0.0181943625
## Lag 4e+05 -0.014192490                     0.0250638948
## Lag 5e+05  0.011403172                     0.0033216114
##           nodefactor.deg.main.deg.pers.0.2
## Lag 0                         1.0000000000
## Lag 1e+05                    -0.0107765264
## Lag 2e+05                     0.0078438985
## Lag 3e+05                    -0.0008727871
## Lag 4e+05                    -0.0053017389
## Lag 5e+05                    -0.0290987013
##           nodefactor.deg.main.deg.pers.1.0
## Lag 0                          1.000000000
## Lag 1e+05                     -0.008305480
## Lag 2e+05                     -0.003069145
## Lag 3e+05                     -0.027181482
## Lag 4e+05                     -0.025797107
## Lag 5e+05                     -0.002132888
##           nodefactor.deg.main.deg.pers.1.1
## Lag 0                          1.000000000
## Lag 1e+05                      0.011000145
## Lag 2e+05                     -0.010774679
## Lag 3e+05                      0.014422446
## Lag 4e+05                     -0.003528089
## Lag 5e+05                     -0.016561240
##           nodefactor.deg.main.deg.pers.1.2 nodefactor.race..wa.B
## Lag 0                           1.00000000           1.000000000
## Lag 1e+05                       0.00560792           0.014302886
## Lag 2e+05                       0.01837006          -0.004619584
## Lag 3e+05                      -0.02901384           0.009385448
## Lag 4e+05                       0.00756092           0.013721063
## Lag 5e+05                       0.01549756          -0.006721578
##           nodefactor.race..wa.H nodefactor.region.EW nodefactor.region.OW
## Lag 0               1.000000000          1.000000000          1.000000000
## Lag 1e+05           0.011441087          0.021936568          0.004116709
## Lag 2e+05          -0.011396975         -0.005897103          0.001635803
## Lag 3e+05           0.003639141          0.003283407          0.015200212
## Lag 4e+05          -0.021862893         -0.015692110         -0.017249396
## Lag 5e+05           0.002734913          0.020993150         -0.008730709
##           nodematch.race..wa.B nodematch.race..wa.H nodematch.race..wa.O
## Lag 0              1.000000000          1.000000000          1.000000000
## Lag 1e+05          0.002961158          0.017331638          0.022400686
## Lag 2e+05         -0.004279574          0.003808839          0.010695344
## Lag 3e+05         -0.007098422          0.023744883          0.036053335
## Lag 4e+05         -0.034010399         -0.007873665         -0.008788388
## Lag 5e+05          0.008476088         -0.009711478         -0.004177706
##           absdiff.sqrt.age
## Lag 0          1.000000000
## Lag 1e+05      0.012993728
## Lag 2e+05     -0.024825080
## Lag 3e+05     -0.021574466
## Lag 4e+05     -0.005599627
## Lag 5e+05      0.005403102
## Chain 7 
##                  edges nodefactor.deg.main.deg.pers.0.1
## Lag 0      1.000000000                     1.0000000000
## Lag 1e+05 -0.007901092                    -0.0128422155
## Lag 2e+05  0.013150909                    -0.0019509213
## Lag 3e+05  0.009631403                    -0.0006970397
## Lag 4e+05 -0.027800953                    -0.0044496533
## Lag 5e+05 -0.020390202                    -0.0127240668
##           nodefactor.deg.main.deg.pers.0.2
## Lag 0                          1.000000000
## Lag 1e+05                     -0.019707210
## Lag 2e+05                     -0.018688493
## Lag 3e+05                     -0.013684223
## Lag 4e+05                     -0.001928193
## Lag 5e+05                     -0.005117483
##           nodefactor.deg.main.deg.pers.1.0
## Lag 0                          1.000000000
## Lag 1e+05                      0.013329969
## Lag 2e+05                      0.012331323
## Lag 3e+05                      0.026714637
## Lag 4e+05                     -0.002936256
## Lag 5e+05                     -0.015961127
##           nodefactor.deg.main.deg.pers.1.1
## Lag 0                          1.000000000
## Lag 1e+05                      0.005756863
## Lag 2e+05                      0.005358271
## Lag 3e+05                      0.008943830
## Lag 4e+05                     -0.003785219
## Lag 5e+05                      0.013954168
##           nodefactor.deg.main.deg.pers.1.2 nodefactor.race..wa.B
## Lag 0                         1.0000000000           1.000000000
## Lag 1e+05                     0.0003420731          -0.006497138
## Lag 2e+05                    -0.0056926857          -0.001744728
## Lag 3e+05                     0.0126847586           0.006471145
## Lag 4e+05                    -0.0080426682          -0.015906986
## Lag 5e+05                    -0.0085963466          -0.024640889
##           nodefactor.race..wa.H nodefactor.region.EW nodefactor.region.OW
## Lag 0               1.000000000          1.000000000          1.000000000
## Lag 1e+05          -0.012618056          0.007941287         -0.003263804
## Lag 2e+05           0.014306991         -0.006917664          0.004609770
## Lag 3e+05          -0.005747867         -0.011066343         -0.008806503
## Lag 4e+05          -0.012314578         -0.020711298          0.018731682
## Lag 5e+05          -0.005871468         -0.001652041         -0.001200922
##           nodematch.race..wa.B nodematch.race..wa.H nodematch.race..wa.O
## Lag 0              1.000000000         1.0000000000          1.000000000
## Lag 1e+05         -0.002603057        -0.0011249083         -0.010077286
## Lag 2e+05          0.003959600        -0.0001576194          0.017815664
## Lag 3e+05          0.010979266        -0.0264310211          0.005596769
## Lag 4e+05         -0.018666901         0.0119213240         -0.001692823
## Lag 5e+05          0.018920308         0.0221700270          0.011709217
##           absdiff.sqrt.age
## Lag 0          1.000000000
## Lag 1e+05     -0.017543734
## Lag 2e+05      0.023846321
## Lag 3e+05      0.002608732
## Lag 4e+05     -0.033589301
## Lag 5e+05     -0.026674610
## Chain 8 
##                  edges nodefactor.deg.main.deg.pers.0.1
## Lag 0      1.000000000                      1.000000000
## Lag 1e+05  0.021138378                      0.020353901
## Lag 2e+05  0.008556820                     -0.001831348
## Lag 3e+05  0.013467476                     -0.003579938
## Lag 4e+05 -0.019258016                     -0.013229369
## Lag 5e+05  0.007876562                      0.003433621
##           nodefactor.deg.main.deg.pers.0.2
## Lag 0                          1.000000000
## Lag 1e+05                     -0.013899941
## Lag 2e+05                      0.020543135
## Lag 3e+05                      0.002466346
## Lag 4e+05                      0.004410165
## Lag 5e+05                      0.010126699
##           nodefactor.deg.main.deg.pers.1.0
## Lag 0                          1.000000000
## Lag 1e+05                     -0.002087121
## Lag 2e+05                     -0.030978972
## Lag 3e+05                      0.003617391
## Lag 4e+05                      0.008572298
## Lag 5e+05                      0.003095679
##           nodefactor.deg.main.deg.pers.1.1
## Lag 0                          1.000000000
## Lag 1e+05                     -0.014227811
## Lag 2e+05                     -0.016187573
## Lag 3e+05                      0.013481054
## Lag 4e+05                      0.008353760
## Lag 5e+05                     -0.007196712
##           nodefactor.deg.main.deg.pers.1.2 nodefactor.race..wa.B
## Lag 0                          1.000000000           1.000000000
## Lag 1e+05                     -0.006306943           0.001559647
## Lag 2e+05                     -0.001843008           0.015856349
## Lag 3e+05                      0.020493279          -0.006634703
## Lag 4e+05                     -0.039019520          -0.012671677
## Lag 5e+05                     -0.013091068          -0.001168916
##           nodefactor.race..wa.H nodefactor.region.EW nodefactor.region.OW
## Lag 0               1.000000000          1.000000000          1.000000000
## Lag 1e+05          -0.003929975          0.008552509          0.027299650
## Lag 2e+05           0.002041159          0.003940562          0.009809759
## Lag 3e+05          -0.012792845          0.012676536         -0.010920789
## Lag 4e+05           0.007043652          0.001140703         -0.001763095
## Lag 5e+05          -0.015995017          0.018210158          0.004851399
##           nodematch.race..wa.B nodematch.race..wa.H nodematch.race..wa.O
## Lag 0              1.000000000         1.000000e+00          1.000000000
## Lag 1e+05         -0.024497069         2.036954e-03          0.020094760
## Lag 2e+05          0.020993021         4.605290e-06         -0.021298149
## Lag 3e+05         -0.002666515        -5.771838e-04          0.020303452
## Lag 4e+05         -0.004576363         2.935633e-02         -0.001221739
## Lag 5e+05         -0.013146089        -9.281761e-03         -0.016015179
##           absdiff.sqrt.age
## Lag 0          1.000000000
## Lag 1e+05      0.019121829
## Lag 2e+05      0.012735967
## Lag 3e+05     -0.027887779
## Lag 4e+05     -0.025727528
## Lag 5e+05      0.001179783
## 
## Sample statistics burn-in diagnostic (Geweke):
## Chain 8 
## 
## Fraction in 1st window = 0.1
## Fraction in 2nd window = 0.5 
## 
##                            edges nodefactor.deg.main.deg.pers.0.1 
##                         -0.28720                         -1.31474 
## nodefactor.deg.main.deg.pers.0.2 nodefactor.deg.main.deg.pers.1.0 
##                         -1.19983                         -0.08850 
## nodefactor.deg.main.deg.pers.1.1 nodefactor.deg.main.deg.pers.1.2 
##                          1.23551                         -1.59674 
##            nodefactor.race..wa.B            nodefactor.race..wa.H 
##                          1.11538                         -0.07941 
##             nodefactor.region.EW             nodefactor.region.OW 
##                         -0.78435                         -0.77976 
##             nodematch.race..wa.B             nodematch.race..wa.H 
##                          1.52970                          0.03975 
##             nodematch.race..wa.O                 absdiff.sqrt.age 
##                         -0.28387                         -0.37169 
## 
## Individual P-values (lower = worse):
##                            edges nodefactor.deg.main.deg.pers.0.1 
##                        0.7739628                        0.1885964 
## nodefactor.deg.main.deg.pers.0.2 nodefactor.deg.main.deg.pers.1.0 
##                        0.2302042                        0.9294773 
## nodefactor.deg.main.deg.pers.1.1 nodefactor.deg.main.deg.pers.1.2 
##                        0.2166402                        0.1103244 
##            nodefactor.race..wa.B            nodefactor.race..wa.H 
##                        0.2646881                        0.9367100 
##             nodefactor.region.EW             nodefactor.region.OW 
##                        0.4328334                        0.4355347 
##             nodematch.race..wa.B             nodematch.race..wa.H 
##                        0.1260912                        0.9682958 
##             nodematch.race..wa.O                 absdiff.sqrt.age 
##                        0.7765076                        0.7101229 
## Joint P-value (lower = worse):  0.9047583 .
## Chain 8 
## 
## Fraction in 1st window = 0.1
## Fraction in 2nd window = 0.5 
## 
##                            edges nodefactor.deg.main.deg.pers.0.1 
##                        -0.829015                        -0.411410 
## nodefactor.deg.main.deg.pers.0.2 nodefactor.deg.main.deg.pers.1.0 
##                        -1.527001                        -0.009976 
## nodefactor.deg.main.deg.pers.1.1 nodefactor.deg.main.deg.pers.1.2 
##                        -0.606915                        -0.806512 
##            nodefactor.race..wa.B            nodefactor.race..wa.H 
##                         0.151949                        -0.875258 
##             nodefactor.region.EW             nodefactor.region.OW 
##                        -0.578872                        -0.436462 
##             nodematch.race..wa.B             nodematch.race..wa.H 
##                         0.751316                         0.090636 
##             nodematch.race..wa.O                 absdiff.sqrt.age 
##                        -0.070677                        -0.730110 
## 
## Individual P-values (lower = worse):
##                            edges nodefactor.deg.main.deg.pers.0.1 
##                        0.4070957                        0.6807718 
## nodefactor.deg.main.deg.pers.0.2 nodefactor.deg.main.deg.pers.1.0 
##                        0.1267608                        0.9920404 
## nodefactor.deg.main.deg.pers.1.1 nodefactor.deg.main.deg.pers.1.2 
##                        0.5439072                        0.4199477 
##            nodefactor.race..wa.B            nodefactor.race..wa.H 
##                        0.8792276                        0.3814337 
##             nodefactor.region.EW             nodefactor.region.OW 
##                        0.5626754                        0.6625017 
##             nodematch.race..wa.B             nodematch.race..wa.H 
##                        0.4524622                        0.9277821 
##             nodematch.race..wa.O                 absdiff.sqrt.age 
##                        0.9436547                        0.4653229 
## Joint P-value (lower = worse):  0.9680146 .
## Chain 8 
## 
## Fraction in 1st window = 0.1
## Fraction in 2nd window = 0.5 
## 
##                            edges nodefactor.deg.main.deg.pers.0.1 
##                          0.40194                         -0.01595 
## nodefactor.deg.main.deg.pers.0.2 nodefactor.deg.main.deg.pers.1.0 
##                          1.72404                          1.75124 
## nodefactor.deg.main.deg.pers.1.1 nodefactor.deg.main.deg.pers.1.2 
##                         -0.37167                          0.86400 
##            nodefactor.race..wa.B            nodefactor.race..wa.H 
##                         -0.44226                         -1.73219 
##             nodefactor.region.EW             nodefactor.region.OW 
##                          0.10679                          0.70563 
##             nodematch.race..wa.B             nodematch.race..wa.H 
##                          0.19376                         -0.07675 
##             nodematch.race..wa.O                 absdiff.sqrt.age 
##                          1.49390                          0.81522 
## 
## Individual P-values (lower = worse):
##                            edges nodefactor.deg.main.deg.pers.0.1 
##                       0.68772906                       0.98727082 
## nodefactor.deg.main.deg.pers.0.2 nodefactor.deg.main.deg.pers.1.0 
##                       0.08470144                       0.07990390 
## nodefactor.deg.main.deg.pers.1.1 nodefactor.deg.main.deg.pers.1.2 
##                       0.71013664                       0.38758913 
##            nodefactor.race..wa.B            nodefactor.race..wa.H 
##                       0.65829897                       0.08323924 
##             nodefactor.region.EW             nodefactor.region.OW 
##                       0.91495670                       0.48041582 
##             nodematch.race..wa.B             nodematch.race..wa.H 
##                       0.84636769                       0.93882221 
##             nodematch.race..wa.O                 absdiff.sqrt.age 
##                       0.13520292                       0.41494443 
## Joint P-value (lower = worse):  0.5940885 .
## Chain 8 
## 
## Fraction in 1st window = 0.1
## Fraction in 2nd window = 0.5 
## 
##                            edges nodefactor.deg.main.deg.pers.0.1 
##                          -0.4184                          -0.1290 
## nodefactor.deg.main.deg.pers.0.2 nodefactor.deg.main.deg.pers.1.0 
##                           0.3174                          -0.3168 
## nodefactor.deg.main.deg.pers.1.1 nodefactor.deg.main.deg.pers.1.2 
##                          -1.2190                           1.2427 
##            nodefactor.race..wa.B            nodefactor.race..wa.H 
##                          -0.4139                          -1.0501 
##             nodefactor.region.EW             nodefactor.region.OW 
##                          -1.9051                           0.5751 
##             nodematch.race..wa.B             nodematch.race..wa.H 
##                           0.4331                          -1.4620 
##             nodematch.race..wa.O                 absdiff.sqrt.age 
##                           0.4120                          -1.1598 
## 
## Individual P-values (lower = worse):
##                            edges nodefactor.deg.main.deg.pers.0.1 
##                       0.67567211                       0.89733231 
## nodefactor.deg.main.deg.pers.0.2 nodefactor.deg.main.deg.pers.1.0 
##                       0.75091388                       0.75136556 
## nodefactor.deg.main.deg.pers.1.1 nodefactor.deg.main.deg.pers.1.2 
##                       0.22282572                       0.21396974 
##            nodefactor.race..wa.B            nodefactor.race..wa.H 
##                       0.67895191                       0.29365049 
##             nodefactor.region.EW             nodefactor.region.OW 
##                       0.05676442                       0.56520890 
##             nodematch.race..wa.B             nodematch.race..wa.H 
##                       0.66492645                       0.14372965 
##             nodematch.race..wa.O                 absdiff.sqrt.age 
##                       0.68033499                       0.24614527 
## Joint P-value (lower = worse):  0.6646768 .
## Chain 8 
## 
## Fraction in 1st window = 0.1
## Fraction in 2nd window = 0.5 
## 
##                            edges nodefactor.deg.main.deg.pers.0.1 
##                          0.27805                         -0.12605 
## nodefactor.deg.main.deg.pers.0.2 nodefactor.deg.main.deg.pers.1.0 
##                         -0.94053                          2.83070 
## nodefactor.deg.main.deg.pers.1.1 nodefactor.deg.main.deg.pers.1.2 
##                         -1.36660                         -0.08537 
##            nodefactor.race..wa.B            nodefactor.race..wa.H 
##                         -0.21573                         -0.89710 
##             nodefactor.region.EW             nodefactor.region.OW 
##                          2.35538                         -1.12601 
##             nodematch.race..wa.B             nodematch.race..wa.H 
##                          0.22372                          0.29679 
##             nodematch.race..wa.O                 absdiff.sqrt.age 
##                          0.74658                          0.65210 
## 
## Individual P-values (lower = worse):
##                            edges nodefactor.deg.main.deg.pers.0.1 
##                      0.780975482                      0.899693310 
## nodefactor.deg.main.deg.pers.0.2 nodefactor.deg.main.deg.pers.1.0 
##                      0.346945246                      0.004644651 
## nodefactor.deg.main.deg.pers.1.1 nodefactor.deg.main.deg.pers.1.2 
##                      0.171749704                      0.931967679 
##            nodefactor.race..wa.B            nodefactor.race..wa.H 
##                      0.829197425                      0.369664846 
##             nodefactor.region.EW             nodefactor.region.OW 
##                      0.018503787                      0.260161965 
##             nodematch.race..wa.B             nodematch.race..wa.H 
##                      0.822972775                      0.766628497 
##             nodematch.race..wa.O                 absdiff.sqrt.age 
##                      0.455320041                      0.514334193 
## Joint P-value (lower = worse):  0.3632008 .
## Chain 8 
## 
## Fraction in 1st window = 0.1
## Fraction in 2nd window = 0.5 
## 
##                            edges nodefactor.deg.main.deg.pers.0.1 
##                           2.2718                           1.9141 
## nodefactor.deg.main.deg.pers.0.2 nodefactor.deg.main.deg.pers.1.0 
##                           1.4310                           0.6521 
## nodefactor.deg.main.deg.pers.1.1 nodefactor.deg.main.deg.pers.1.2 
##                           0.9718                           1.4300 
##            nodefactor.race..wa.B            nodefactor.race..wa.H 
##                          -0.5751                           1.5276 
##             nodefactor.region.EW             nodefactor.region.OW 
##                           1.2643                           0.6554 
##             nodematch.race..wa.B             nodematch.race..wa.H 
##                          -0.1282                           1.5610 
##             nodematch.race..wa.O                 absdiff.sqrt.age 
##                           2.6162                           0.5426 
## 
## Individual P-values (lower = worse):
##                            edges nodefactor.deg.main.deg.pers.0.1 
##                      0.023097780                      0.055607649 
## nodefactor.deg.main.deg.pers.0.2 nodefactor.deg.main.deg.pers.1.0 
##                      0.152439262                      0.514307403 
## nodefactor.deg.main.deg.pers.1.1 nodefactor.deg.main.deg.pers.1.2 
##                      0.331163232                      0.152725477 
##            nodefactor.race..wa.B            nodefactor.race..wa.H 
##                      0.565200383                      0.126618330 
##             nodefactor.region.EW             nodefactor.region.OW 
##                      0.206121583                      0.512222705 
##             nodematch.race..wa.B             nodematch.race..wa.H 
##                      0.897999785                      0.118516933 
##             nodematch.race..wa.O                 absdiff.sqrt.age 
##                      0.008891021                      0.587392959 
## Joint P-value (lower = worse):  0.6223076 .
## Chain 8 
## 
## Fraction in 1st window = 0.1
## Fraction in 2nd window = 0.5 
## 
##                            edges nodefactor.deg.main.deg.pers.0.1 
##                         -0.20650                         -0.06224 
## nodefactor.deg.main.deg.pers.0.2 nodefactor.deg.main.deg.pers.1.0 
##                         -0.36688                         -0.65690 
## nodefactor.deg.main.deg.pers.1.1 nodefactor.deg.main.deg.pers.1.2 
##                         -0.11850                         -0.79751 
##            nodefactor.race..wa.B            nodefactor.race..wa.H 
##                         -0.67853                         -1.86867 
##             nodefactor.region.EW             nodefactor.region.OW 
##                         -0.19532                         -0.04435 
##             nodematch.race..wa.B             nodematch.race..wa.H 
##                         -2.21051                         -1.78936 
##             nodematch.race..wa.O                 absdiff.sqrt.age 
##                          0.92439                         -0.28279 
## 
## Individual P-values (lower = worse):
##                            edges nodefactor.deg.main.deg.pers.0.1 
##                       0.83639991                       0.95036835 
## nodefactor.deg.main.deg.pers.0.2 nodefactor.deg.main.deg.pers.1.0 
##                       0.71371045                       0.51124742 
## nodefactor.deg.main.deg.pers.1.1 nodefactor.deg.main.deg.pers.1.2 
##                       0.90567205                       0.42515264 
##            nodefactor.race..wa.B            nodefactor.race..wa.H 
##                       0.49743836                       0.06166879 
##             nodefactor.region.EW             nodefactor.region.OW 
##                       0.84514572                       0.96462535 
##             nodematch.race..wa.B             nodematch.race..wa.H 
##                       0.02706964                       0.07355687 
##             nodematch.race..wa.O                 absdiff.sqrt.age 
##                       0.35528255                       0.77733421 
## Joint P-value (lower = worse):  0.9164804 .
## Chain 8 
## 
## Fraction in 1st window = 0.1
## Fraction in 2nd window = 0.5 
## 
##                            edges nodefactor.deg.main.deg.pers.0.1 
##                           0.5203                          -0.2522 
## nodefactor.deg.main.deg.pers.0.2 nodefactor.deg.main.deg.pers.1.0 
##                          -0.3955                           1.7603 
## nodefactor.deg.main.deg.pers.1.1 nodefactor.deg.main.deg.pers.1.2 
##                          -0.7848                           0.6090 
##            nodefactor.race..wa.B            nodefactor.race..wa.H 
##                           0.1761                          -0.6157 
##             nodefactor.region.EW             nodefactor.region.OW 
##                          -0.7046                           0.9444 
##             nodematch.race..wa.B             nodematch.race..wa.H 
##                           0.7474                           0.4555 
##             nodematch.race..wa.O                 absdiff.sqrt.age 
##                           0.9814                          -0.7766 
## 
## Individual P-values (lower = worse):
##                            edges nodefactor.deg.main.deg.pers.0.1 
##                        0.6028833                        0.8008482 
## nodefactor.deg.main.deg.pers.0.2 nodefactor.deg.main.deg.pers.1.0 
##                        0.6924599                        0.0783584 
## nodefactor.deg.main.deg.pers.1.1 nodefactor.deg.main.deg.pers.1.2 
##                        0.4325754                        0.5425482 
##            nodefactor.race..wa.B            nodefactor.race..wa.H 
##                        0.8602167                        0.5380992 
##             nodefactor.region.EW             nodefactor.region.OW 
##                        0.4810359                        0.3449738 
##             nodematch.race..wa.B             nodematch.race..wa.H 
##                        0.4548377                        0.6487240 
##             nodematch.race..wa.O                 absdiff.sqrt.age 
##                        0.3264055                        0.4374197 
## Joint P-value (lower = worse):  0.7827664 .
## Warning in formals(fun): argument is not a function

## 
## MCMC diagnostics shown here are from the last round of simulation, prior to computation of final parameter estimates. Because the final estimates are refinements of those used for this simulation run, these diagnostics may understate model performance. To directly assess the performance of the final model on in-model statistics, please use the GOF command: gof(ergmFitObject, GOF=~model).

Model 7

## Sample statistics summary:
## 
## Iterations = 1e+06:375900000
## Thinning interval = 1e+05 
## Number of chains = 8 
## Sample size per chain = 3750 
## 
## 1. Empirical mean and standard deviation for each variable,
##    plus standard error of the mean:
## 
##                                       Mean     SD Naive SE Time-series SE
## edges                             1.551413 21.896 0.126416        0.14822
## nodefactor.deg.main.deg.pers.0.1  0.419227 14.240 0.082212        0.10988
## nodefactor.deg.main.deg.pers.0.2  0.133133  6.181 0.035685        0.03628
## nodefactor.deg.main.deg.pers.1.0  0.008829  6.315 0.036460        0.03640
## nodefactor.deg.main.deg.pers.1.1 -0.101231 12.392 0.071544        0.09784
## nodefactor.deg.main.deg.pers.1.2 -0.103491 12.951 0.074772        0.10293
## nodefactor.riskg.O3               0.020816  2.642 0.015252        0.01532
## nodefactor.riskg.O4               1.208370 11.716 0.067645        0.07400
## nodefactor.riskg.Y2              -0.047343  2.867 0.016555        0.01667
## nodefactor.riskg.Y3              -0.074032  8.699 0.050223        0.04970
## nodefactor.race..wa.B             0.416284  9.004 0.051983        0.06790
## nodefactor.race..wa.H             0.666647 13.349 0.077070        0.11407
## nodefactor.region.EW              0.932858  9.604 0.055450        0.06457
## nodefactor.region.OW              0.590727 17.467 0.100846        0.11520
## nodematch.race..wa.B              0.190249  1.658 0.009572        0.01229
## nodematch.race..wa.H              0.199580  3.668 0.021178        0.03516
## nodematch.race..wa.O              0.835044 16.971 0.097982        0.11278
## absdiff.sqrt.age                  2.550655 22.497 0.129886        0.13852
## 
## 2. Quantiles for each variable:
## 
##                                     2.5%      25%      50%    75%  97.5%
## edges                            -40.159 -13.1586  0.84138 15.841 44.841
## nodefactor.deg.main.deg.pers.0.1 -26.310  -9.3100 -0.31004  9.690 28.715
## nodefactor.deg.main.deg.pers.0.2 -11.371  -4.3710 -0.37103  4.629 12.629
## nodefactor.deg.main.deg.pers.1.0 -12.033  -4.0335 -0.03347  3.967 12.967
## nodefactor.deg.main.deg.pers.1.1 -23.538  -8.5379 -0.53786  8.462 25.462
## nodefactor.deg.main.deg.pers.1.2 -24.388  -9.3881 -0.38812  8.612 25.612
## nodefactor.riskg.O3               -4.856  -1.8558  0.14418  2.144  5.144
## nodefactor.riskg.O4              -20.513  -6.5127  1.48734  8.487 24.487
## nodefactor.riskg.Y2               -5.202  -2.2024 -0.20238  1.798  5.798
## nodefactor.riskg.Y3              -16.786  -5.7860  0.21403  6.214 17.214
## nodefactor.race..wa.B            -16.591  -5.5908  0.40918  6.409 18.409
## nodefactor.race..wa.H            -25.174  -8.1739  0.82608  9.826 27.826
## nodefactor.region.EW             -17.501  -5.5014  0.49862  7.499 20.499
## nodefactor.region.OW             -32.486 -11.4862  0.51379 12.514 35.514
## nodematch.race..wa.B              -2.540  -0.5399  0.46015  1.460  3.460
## nodematch.race..wa.H              -6.269  -2.2690 -0.26902  2.731  7.731
## nodematch.race..wa.O             -31.880 -10.8800  1.11998 12.120 35.120
## absdiff.sqrt.age                 -40.664 -12.8877  2.17723 17.676 47.694
## 
## 
## Sample statistics cross-correlations:
##                                       edges
## edges                            1.00000000
## nodefactor.deg.main.deg.pers.0.1 0.55079177
## nodefactor.deg.main.deg.pers.0.2 0.27985803
## nodefactor.deg.main.deg.pers.1.0 0.28363095
## nodefactor.deg.main.deg.pers.1.1 0.49715069
## nodefactor.deg.main.deg.pers.1.2 0.51273448
## nodefactor.riskg.O3              0.11468086
## nodefactor.riskg.O4              0.42745017
## nodefactor.riskg.Y2              0.12482481
## nodefactor.riskg.Y3              0.37591674
## nodefactor.race..wa.B            0.37239944
## nodefactor.race..wa.H            0.51428535
## nodefactor.region.EW             0.40133906
## nodefactor.region.OW             0.63523544
## nodematch.race..wa.B             0.07862664
## nodematch.race..wa.H             0.17011344
## nodematch.race..wa.O             0.77359501
## absdiff.sqrt.age                 0.77440939
##                                  nodefactor.deg.main.deg.pers.0.1
## edges                                                  0.55079177
## nodefactor.deg.main.deg.pers.0.1                       1.00000000
## nodefactor.deg.main.deg.pers.0.2                       0.08083147
## nodefactor.deg.main.deg.pers.1.0                       0.08411097
## nodefactor.deg.main.deg.pers.1.1                       0.13805665
## nodefactor.deg.main.deg.pers.1.2                       0.13935626
## nodefactor.riskg.O3                                    0.06548722
## nodefactor.riskg.O4                                    0.24042426
## nodefactor.riskg.Y2                                    0.06056040
## nodefactor.riskg.Y3                                    0.19452421
## nodefactor.race..wa.B                                  0.25014081
## nodefactor.race..wa.H                                  0.21413937
## nodefactor.region.EW                                   0.19988488
## nodefactor.region.OW                                   0.38818301
## nodematch.race..wa.B                                   0.05509942
## nodematch.race..wa.H                                   0.04274979
## nodematch.race..wa.O                                   0.44710570
## absdiff.sqrt.age                                       0.42841762
##                                  nodefactor.deg.main.deg.pers.0.2
## edges                                                  0.27985803
## nodefactor.deg.main.deg.pers.0.1                       0.08083147
## nodefactor.deg.main.deg.pers.0.2                       1.00000000
## nodefactor.deg.main.deg.pers.1.0                       0.04203955
## nodefactor.deg.main.deg.pers.1.1                       0.07621989
## nodefactor.deg.main.deg.pers.1.2                       0.07708548
## nodefactor.riskg.O3                                    0.02533878
## nodefactor.riskg.O4                                    0.12092259
## nodefactor.riskg.Y2                                    0.03717978
## nodefactor.riskg.Y3                                    0.11013557
## nodefactor.race..wa.B                                  0.11745126
## nodefactor.race..wa.H                                  0.14247019
## nodefactor.region.EW                                   0.08448266
## nodefactor.region.OW                                   0.17505361
## nodematch.race..wa.B                                   0.02775291
## nodematch.race..wa.H                                   0.04654421
## nodematch.race..wa.O                                   0.21172315
## absdiff.sqrt.age                                       0.21719572
##                                  nodefactor.deg.main.deg.pers.1.0
## edges                                                 0.283630946
## nodefactor.deg.main.deg.pers.0.1                      0.084110972
## nodefactor.deg.main.deg.pers.0.2                      0.042039546
## nodefactor.deg.main.deg.pers.1.0                      1.000000000
## nodefactor.deg.main.deg.pers.1.1                      0.073465047
## nodefactor.deg.main.deg.pers.1.2                      0.069585160
## nodefactor.riskg.O3                                   0.034538180
## nodefactor.riskg.O4                                   0.128899376
## nodefactor.riskg.Y2                                   0.032027043
## nodefactor.riskg.Y3                                   0.101567284
## nodefactor.race..wa.B                                 0.089414751
## nodefactor.race..wa.H                                 0.175407892
## nodefactor.region.EW                                  0.126322910
## nodefactor.region.OW                                  0.174718646
## nodematch.race..wa.B                                  0.004013376
## nodematch.race..wa.H                                  0.064794176
## nodematch.race..wa.O                                  0.207849361
## absdiff.sqrt.age                                      0.218926028
##                                  nodefactor.deg.main.deg.pers.1.1
## edges                                                  0.49715069
## nodefactor.deg.main.deg.pers.0.1                       0.13805665
## nodefactor.deg.main.deg.pers.0.2                       0.07621989
## nodefactor.deg.main.deg.pers.1.0                       0.07346505
## nodefactor.deg.main.deg.pers.1.1                       1.00000000
## nodefactor.deg.main.deg.pers.1.2                       0.13527626
## nodefactor.riskg.O3                                    0.06463869
## nodefactor.riskg.O4                                    0.19285052
## nodefactor.riskg.Y2                                    0.06311208
## nodefactor.riskg.Y3                                    0.19695141
## nodefactor.race..wa.B                                  0.16784921
## nodefactor.race..wa.H                                  0.28731343
## nodefactor.region.EW                                   0.18946314
## nodefactor.region.OW                                   0.32599534
## nodematch.race..wa.B                                   0.03654982
## nodematch.race..wa.H                                   0.10700459
## nodematch.race..wa.O                                   0.37335186
## absdiff.sqrt.age                                       0.37185967
##                                  nodefactor.deg.main.deg.pers.1.2
## edges                                                  0.51273448
## nodefactor.deg.main.deg.pers.0.1                       0.13935626
## nodefactor.deg.main.deg.pers.0.2                       0.07708548
## nodefactor.deg.main.deg.pers.1.0                       0.06958516
## nodefactor.deg.main.deg.pers.1.1                       0.13527626
## nodefactor.deg.main.deg.pers.1.2                       1.00000000
## nodefactor.riskg.O3                                    0.05661469
## nodefactor.riskg.O4                                    0.21560734
## nodefactor.riskg.Y2                                    0.08141334
## nodefactor.riskg.Y3                                    0.20139001
## nodefactor.race..wa.B                                  0.12180411
## nodefactor.race..wa.H                                  0.32417273
## nodefactor.region.EW                                   0.24525850
## nodefactor.region.OW                                   0.30125716
## nodematch.race..wa.B                                   0.01553903
## nodematch.race..wa.H                                   0.13192455
## nodematch.race..wa.O                                   0.38929938
## absdiff.sqrt.age                                       0.39501466
##                                  nodefactor.riskg.O3 nodefactor.riskg.O4
## edges                                    0.114680858          0.42745017
## nodefactor.deg.main.deg.pers.0.1         0.065487218          0.24042426
## nodefactor.deg.main.deg.pers.0.2         0.025338778          0.12092259
## nodefactor.deg.main.deg.pers.1.0         0.034538180          0.12889938
## nodefactor.deg.main.deg.pers.1.1         0.064638685          0.19285052
## nodefactor.deg.main.deg.pers.1.2         0.056614689          0.21560734
## nodefactor.riskg.O3                      1.000000000          0.05078592
## nodefactor.riskg.O4                      0.050785917          1.00000000
## nodefactor.riskg.Y2                      0.002951720          0.02254111
## nodefactor.riskg.Y3                      0.018259488          0.05964692
## nodefactor.race..wa.B                    0.033601211          0.17516599
## nodefactor.race..wa.H                    0.061804666          0.26532361
## nodefactor.region.EW                     0.045782430          0.16608973
## nodefactor.region.OW                     0.073539239          0.27847081
## nodematch.race..wa.B                     0.007178089          0.03422864
## nodematch.race..wa.H                     0.018634883          0.10602910
## nodematch.race..wa.O                     0.090137441          0.29839430
## absdiff.sqrt.age                         0.116451900          0.43038125
##                                  nodefactor.riskg.Y2 nodefactor.riskg.Y3
## edges                                    0.124824807          0.37591674
## nodefactor.deg.main.deg.pers.0.1         0.060560405          0.19452421
## nodefactor.deg.main.deg.pers.0.2         0.037179782          0.11013557
## nodefactor.deg.main.deg.pers.1.0         0.032027043          0.10156728
## nodefactor.deg.main.deg.pers.1.1         0.063112075          0.19695141
## nodefactor.deg.main.deg.pers.1.2         0.081413338          0.20139001
## nodefactor.riskg.O3                      0.002951720          0.01825949
## nodefactor.riskg.O4                      0.022541108          0.05964692
## nodefactor.riskg.Y2                      1.000000000          0.01644260
## nodefactor.riskg.Y3                      0.016442599          1.00000000
## nodefactor.race..wa.B                    0.046047909          0.12697607
## nodefactor.race..wa.H                    0.073718183          0.18581141
## nodefactor.region.EW                     0.051822298          0.15067833
## nodefactor.region.OW                     0.077282826          0.23338907
## nodematch.race..wa.B                    -0.003482857          0.01781101
## nodematch.race..wa.H                     0.028923158          0.06137097
## nodematch.race..wa.O                     0.090299049          0.30057440
## absdiff.sqrt.age                         0.091658867          0.28221988
##                                  nodefactor.race..wa.B
## edges                                      0.372399440
## nodefactor.deg.main.deg.pers.0.1           0.250140813
## nodefactor.deg.main.deg.pers.0.2           0.117451258
## nodefactor.deg.main.deg.pers.1.0           0.089414751
## nodefactor.deg.main.deg.pers.1.1           0.167849213
## nodefactor.deg.main.deg.pers.1.2           0.121804107
## nodefactor.riskg.O3                        0.033601211
## nodefactor.riskg.O4                        0.175165990
## nodefactor.riskg.Y2                        0.046047909
## nodefactor.riskg.Y3                        0.126976070
## nodefactor.race..wa.B                      1.000000000
## nodefactor.race..wa.H                      0.122780010
## nodefactor.region.EW                       0.108802884
## nodefactor.region.OW                       0.189664105
## nodematch.race..wa.B                       0.373048675
## nodematch.race..wa.H                      -0.008226545
## nodematch.race..wa.O                      -0.007309730
## absdiff.sqrt.age                           0.290756194
##                                  nodefactor.race..wa.H
## edges                                      0.514285349
## nodefactor.deg.main.deg.pers.0.1           0.214139374
## nodefactor.deg.main.deg.pers.0.2           0.142470192
## nodefactor.deg.main.deg.pers.1.0           0.175407892
## nodefactor.deg.main.deg.pers.1.1           0.287313425
## nodefactor.deg.main.deg.pers.1.2           0.324172726
## nodefactor.riskg.O3                        0.061804666
## nodefactor.riskg.O4                        0.265323609
## nodefactor.riskg.Y2                        0.073718183
## nodefactor.riskg.Y3                        0.185811407
## nodefactor.race..wa.B                      0.122780010
## nodefactor.race..wa.H                      1.000000000
## nodefactor.region.EW                       0.312281974
## nodefactor.region.OW                       0.280484856
## nodematch.race..wa.B                      -0.001287749
## nodematch.race..wa.H                       0.555302439
## nodematch.race..wa.O                       0.001677746
## absdiff.sqrt.age                           0.402152227
##                                  nodefactor.region.EW nodefactor.region.OW
## edges                                     0.401339060           0.63523544
## nodefactor.deg.main.deg.pers.0.1          0.199884875           0.38818301
## nodefactor.deg.main.deg.pers.0.2          0.084482659           0.17505361
## nodefactor.deg.main.deg.pers.1.0          0.126322910           0.17471865
## nodefactor.deg.main.deg.pers.1.1          0.189463136           0.32599534
## nodefactor.deg.main.deg.pers.1.2          0.245258502           0.30125716
## nodefactor.riskg.O3                       0.045782430           0.07353924
## nodefactor.riskg.O4                       0.166089730           0.27847081
## nodefactor.riskg.Y2                       0.051822298           0.07728283
## nodefactor.riskg.Y3                       0.150678328           0.23338907
## nodefactor.race..wa.B                     0.108802884           0.18966411
## nodefactor.race..wa.H                     0.312281974           0.28048486
## nodefactor.region.EW                      1.000000000           0.12154771
## nodefactor.region.OW                      0.121547706           1.00000000
## nodematch.race..wa.B                      0.009163413           0.03164809
## nodematch.race..wa.H                      0.132339507           0.08409190
## nodematch.race..wa.O                      0.263771580           0.53652501
## absdiff.sqrt.age                          0.305178000           0.48271453
##                                  nodematch.race..wa.B nodematch.race..wa.H
## edges                                     0.078626638          0.170113440
## nodefactor.deg.main.deg.pers.0.1          0.055099416          0.042749793
## nodefactor.deg.main.deg.pers.0.2          0.027752907          0.046544214
## nodefactor.deg.main.deg.pers.1.0          0.004013376          0.064794176
## nodefactor.deg.main.deg.pers.1.1          0.036549820          0.107004588
## nodefactor.deg.main.deg.pers.1.2          0.015539029          0.131924545
## nodefactor.riskg.O3                       0.007178089          0.018634883
## nodefactor.riskg.O4                       0.034228640          0.106029100
## nodefactor.riskg.Y2                      -0.003482857          0.028923158
## nodefactor.riskg.Y3                       0.017811007          0.061370969
## nodefactor.race..wa.B                     0.373048675         -0.008226545
## nodefactor.race..wa.H                    -0.001287749          0.555302439
## nodefactor.region.EW                      0.009163413          0.132339507
## nodefactor.region.OW                      0.031648093          0.084091905
## nodematch.race..wa.B                      1.000000000         -0.006450259
## nodematch.race..wa.H                     -0.006450259          1.000000000
## nodematch.race..wa.O                      0.001929891          0.001497485
## absdiff.sqrt.age                          0.061812679          0.131601166
##                                  nodematch.race..wa.O absdiff.sqrt.age
## edges                                     0.773595014       0.77440939
## nodefactor.deg.main.deg.pers.0.1          0.447105704       0.42841762
## nodefactor.deg.main.deg.pers.0.2          0.211723152       0.21719572
## nodefactor.deg.main.deg.pers.1.0          0.207849361       0.21892603
## nodefactor.deg.main.deg.pers.1.1          0.373351859       0.37185967
## nodefactor.deg.main.deg.pers.1.2          0.389299376       0.39501466
## nodefactor.riskg.O3                       0.090137441       0.11645190
## nodefactor.riskg.O4                       0.298394300       0.43038125
## nodefactor.riskg.Y2                       0.090299049       0.09165887
## nodefactor.riskg.Y3                       0.300574400       0.28221988
## nodefactor.race..wa.B                    -0.007309730       0.29075619
## nodefactor.race..wa.H                     0.001677746       0.40215223
## nodefactor.region.EW                      0.263771580       0.30517800
## nodefactor.region.OW                      0.536525005       0.48271453
## nodematch.race..wa.B                      0.001929891       0.06181268
## nodematch.race..wa.H                      0.001497485       0.13160117
## nodematch.race..wa.O                      1.000000000       0.59632515
## absdiff.sqrt.age                          0.596325146       1.00000000
## 
## Sample statistics auto-correlation:
## Chain 1 
##                  edges nodefactor.deg.main.deg.pers.0.1
## Lag 0      1.000000000                       1.00000000
## Lag 1e+05  0.123245833                       0.24800695
## Lag 2e+05  0.046870328                       0.10857276
## Lag 3e+05  0.026452153                       0.05382357
## Lag 4e+05 -0.008684585                       0.02101100
## Lag 5e+05 -0.004726233                       0.02159682
##           nodefactor.deg.main.deg.pers.0.2
## Lag 0                           1.00000000
## Lag 1e+05                       0.02416564
## Lag 2e+05                       0.02069764
## Lag 3e+05                      -0.00389325
## Lag 4e+05                      -0.02110662
## Lag 5e+05                      -0.02940964
##           nodefactor.deg.main.deg.pers.1.0
## Lag 0                         1.0000000000
## Lag 1e+05                     0.0087516356
## Lag 2e+05                    -0.0004742542
## Lag 3e+05                     0.0088293490
## Lag 4e+05                    -0.0049236004
## Lag 5e+05                     0.0028951513
##           nodefactor.deg.main.deg.pers.1.1
## Lag 0                           1.00000000
## Lag 1e+05                       0.21782606
## Lag 2e+05                       0.10764522
## Lag 3e+05                       0.08430781
## Lag 4e+05                       0.05170285
## Lag 5e+05                       0.02074778
##           nodefactor.deg.main.deg.pers.1.2 nodefactor.riskg.O3
## Lag 0                          1.000000000         1.000000000
## Lag 1e+05                      0.248446954        -0.006347544
## Lag 2e+05                      0.121576418        -0.030049606
## Lag 3e+05                      0.070816750         0.002415947
## Lag 4e+05                      0.038911689        -0.001036293
## Lag 5e+05                     -0.001616253         0.004866287
##           nodefactor.riskg.O4 nodefactor.riskg.Y2 nodefactor.riskg.Y3
## Lag 0             1.000000000        1.0000000000        1.0000000000
## Lag 1e+05         0.066710319        0.0013868523       -0.0131090310
## Lag 2e+05         0.025726856        0.0009062492        0.0202971529
## Lag 3e+05         0.002660957       -0.0241959682       -0.0135619196
## Lag 4e+05         0.013992293       -0.0051456530        0.0054744037
## Lag 5e+05        -0.029364955        0.0027193701       -0.0009242468
##           nodefactor.race..wa.B nodefactor.race..wa.H nodefactor.region.EW
## Lag 0               1.000000000            1.00000000          1.000000000
## Lag 1e+05           0.170597873            0.24186789          0.095311762
## Lag 2e+05           0.070733873            0.12295270          0.045694114
## Lag 3e+05           0.045379900            0.07773534          0.020718961
## Lag 4e+05           0.023254784            0.02210548          0.011640553
## Lag 5e+05          -0.001897973            0.04024069          0.008141718
##           nodefactor.region.OW nodematch.race..wa.B nodematch.race..wa.H
## Lag 0              1.000000000           1.00000000           1.00000000
## Lag 1e+05          0.103920129           0.20596672           0.33548573
## Lag 2e+05          0.013802601           0.08618305           0.19182749
## Lag 3e+05         -0.025875110           0.02098423           0.12130230
## Lag 4e+05         -0.009746492           0.03241847           0.05499597
## Lag 5e+05         -0.013232130           0.01380033           0.05315805
##           nodematch.race..wa.O absdiff.sqrt.age
## Lag 0              1.000000000       1.00000000
## Lag 1e+05          0.123830731       0.06072332
## Lag 2e+05          0.019024539       0.02525327
## Lag 3e+05          0.015227993      -0.00337865
## Lag 4e+05         -0.007478674      -0.02161288
## Lag 5e+05         -0.009288200      -0.01810498
## Chain 2 
##                   edges nodefactor.deg.main.deg.pers.0.1
## Lag 0      1.0000000000                       1.00000000
## Lag 1e+05  0.1610350193                       0.22435393
## Lag 2e+05  0.0572814021                       0.11513577
## Lag 3e+05  0.0320105449                       0.07549491
## Lag 4e+05 -0.0009286636                       0.03533366
## Lag 5e+05  0.0070893378                       0.01611871
##           nodefactor.deg.main.deg.pers.0.2
## Lag 0                          1.000000000
## Lag 1e+05                      0.027172414
## Lag 2e+05                      0.010232045
## Lag 3e+05                     -0.019801252
## Lag 4e+05                     -0.031336872
## Lag 5e+05                     -0.004015089
##           nodefactor.deg.main.deg.pers.1.0
## Lag 0                         1.0000000000
## Lag 1e+05                     0.0161856443
## Lag 2e+05                     0.0001069805
## Lag 3e+05                    -0.0231410463
## Lag 4e+05                    -0.0078074880
## Lag 5e+05                     0.0215900601
##           nodefactor.deg.main.deg.pers.1.1
## Lag 0                           1.00000000
## Lag 1e+05                       0.25300287
## Lag 2e+05                       0.09601969
## Lag 3e+05                       0.03935970
## Lag 4e+05                       0.04112870
## Lag 5e+05                       0.01333916
##           nodefactor.deg.main.deg.pers.1.2 nodefactor.riskg.O3
## Lag 0                           1.00000000         1.000000000
## Lag 1e+05                       0.24240021         0.041662608
## Lag 2e+05                       0.11850262         0.025405389
## Lag 3e+05                       0.05482208         0.006474406
## Lag 4e+05                       0.01996231        -0.007867317
## Lag 5e+05                       0.01411700        -0.003991758
##           nodefactor.riskg.O4 nodefactor.riskg.Y2 nodefactor.riskg.Y3
## Lag 0             1.000000000         1.000000000         1.000000000
## Lag 1e+05         0.051940021        -0.009789975        -0.003179577
## Lag 2e+05         0.039739624        -0.020562410         0.003423918
## Lag 3e+05         0.003468693         0.009743931         0.028722165
## Lag 4e+05         0.025806080        -0.009758638         0.005794442
## Lag 5e+05         0.004996162         0.007011462        -0.006353989
##           nodefactor.race..wa.B nodefactor.race..wa.H nodefactor.region.EW
## Lag 0                1.00000000            1.00000000          1.000000000
## Lag 1e+05            0.18390284            0.22461124          0.118126001
## Lag 2e+05            0.10579155            0.10284306          0.006027581
## Lag 3e+05            0.07440813            0.04858804          0.001043890
## Lag 4e+05            0.02767747            0.04537874          0.011787779
## Lag 5e+05            0.01847206            0.02157661         -0.006509702
##           nodefactor.region.OW nodematch.race..wa.B nodematch.race..wa.H
## Lag 0              1.000000000          1.000000000           1.00000000
## Lag 1e+05          0.131030980          0.172495781           0.31905435
## Lag 2e+05          0.048651206          0.076487261           0.15563427
## Lag 3e+05          0.032892552          0.021061321           0.09577794
## Lag 4e+05         -0.007977758          0.016481893           0.06373729
## Lag 5e+05         -0.010671105          0.009336264           0.04127646
##           nodematch.race..wa.O absdiff.sqrt.age
## Lag 0              1.000000000      1.000000000
## Lag 1e+05          0.129161177      0.059528475
## Lag 2e+05          0.027332606      0.016354335
## Lag 3e+05          0.023170935     -0.019169320
## Lag 4e+05         -0.006566014     -0.008201786
## Lag 5e+05          0.008384330      0.003456119
## Chain 3 
##                  edges nodefactor.deg.main.deg.pers.0.1
## Lag 0      1.000000000                       1.00000000
## Lag 1e+05  0.142355042                       0.23795789
## Lag 2e+05  0.038362703                       0.10207609
## Lag 3e+05  0.031015468                       0.04895570
## Lag 4e+05 -0.001053687                       0.01271543
## Lag 5e+05  0.014059458                      -0.01160997
##           nodefactor.deg.main.deg.pers.0.2
## Lag 0                          1.000000000
## Lag 1e+05                      0.028057804
## Lag 2e+05                     -0.003742006
## Lag 3e+05                      0.002598684
## Lag 4e+05                      0.014984398
## Lag 5e+05                     -0.017902204
##           nodefactor.deg.main.deg.pers.1.0
## Lag 0                          1.000000000
## Lag 1e+05                      0.005130196
## Lag 2e+05                      0.013781718
## Lag 3e+05                      0.016086675
## Lag 4e+05                      0.005821366
## Lag 5e+05                      0.004143251
##           nodefactor.deg.main.deg.pers.1.1
## Lag 0                           1.00000000
## Lag 1e+05                       0.24058274
## Lag 2e+05                       0.08809266
## Lag 3e+05                       0.07364258
## Lag 4e+05                       0.03274094
## Lag 5e+05                       0.03195202
##           nodefactor.deg.main.deg.pers.1.2 nodefactor.riskg.O3
## Lag 0                           1.00000000         1.000000000
## Lag 1e+05                       0.24581954        -0.021052138
## Lag 2e+05                       0.09921817        -0.004638132
## Lag 3e+05                       0.06383207         0.003778198
## Lag 4e+05                       0.02825777         0.003870140
## Lag 5e+05                       0.04464453         0.014634347
##           nodefactor.riskg.O4 nodefactor.riskg.Y2 nodefactor.riskg.Y3
## Lag 0              1.00000000         1.000000000          1.00000000
## Lag 1e+05          0.08998512        -0.010222759         -0.01960147
## Lag 2e+05          0.02564090        -0.015634864         -0.01569075
## Lag 3e+05          0.01597810        -0.018629755          0.01373665
## Lag 4e+05          0.01139190        -0.018118400         -0.02766907
## Lag 5e+05         -0.02218312        -0.005953613          0.03823502
##           nodefactor.race..wa.B nodefactor.race..wa.H nodefactor.region.EW
## Lag 0               1.000000000            1.00000000           1.00000000
## Lag 1e+05           0.154511513            0.27630724           0.11518633
## Lag 2e+05           0.075069882            0.14756169           0.07721487
## Lag 3e+05           0.047809949            0.09741470           0.03311641
## Lag 4e+05          -0.003289662            0.05379211          -0.01209963
## Lag 5e+05          -0.007624650            0.04374176           0.01359326
##           nodefactor.region.OW nodematch.race..wa.B nodematch.race..wa.H
## Lag 0              1.000000000           1.00000000           1.00000000
## Lag 1e+05          0.084154894           0.16185503           0.32373668
## Lag 2e+05          0.026780046           0.08798080           0.19858683
## Lag 3e+05          0.027807001           0.03233725           0.11948845
## Lag 4e+05         -0.010732458           0.01860337           0.08835310
## Lag 5e+05          0.008596883           0.02477156           0.06322743
##           nodematch.race..wa.O absdiff.sqrt.age
## Lag 0               1.00000000      1.000000000
## Lag 1e+05           0.10253760      0.069324029
## Lag 2e+05           0.01277395      0.014375316
## Lag 3e+05           0.01665993      0.003268780
## Lag 4e+05           0.02836650     -0.024841298
## Lag 5e+05           0.01458525      0.009135518
## Chain 4 
##                  edges nodefactor.deg.main.deg.pers.0.1
## Lag 0      1.000000000                       1.00000000
## Lag 1e+05  0.122128015                       0.21667641
## Lag 2e+05  0.042606418                       0.08761656
## Lag 3e+05  0.023317945                       0.04193086
## Lag 4e+05 -0.007777635                       0.03207304
## Lag 5e+05  0.018560224                       0.02357198
##           nodefactor.deg.main.deg.pers.0.2
## Lag 0                          1.000000000
## Lag 1e+05                      0.055681567
## Lag 2e+05                      0.006229900
## Lag 3e+05                      0.009811765
## Lag 4e+05                     -0.027102849
## Lag 5e+05                     -0.014119517
##           nodefactor.deg.main.deg.pers.1.0
## Lag 0                          1.000000000
## Lag 1e+05                     -0.003456092
## Lag 2e+05                     -0.001504615
## Lag 3e+05                     -0.012495630
## Lag 4e+05                     -0.011226278
## Lag 5e+05                     -0.003669039
##           nodefactor.deg.main.deg.pers.1.1
## Lag 0                           1.00000000
## Lag 1e+05                       0.25820665
## Lag 2e+05                       0.13685028
## Lag 3e+05                       0.06929471
## Lag 4e+05                       0.03672856
## Lag 5e+05                       0.01947542
##           nodefactor.deg.main.deg.pers.1.2 nodefactor.riskg.O3
## Lag 0                           1.00000000         1.000000000
## Lag 1e+05                       0.22196248        -0.004428586
## Lag 2e+05                       0.09734995        -0.025247719
## Lag 3e+05                       0.03918683         0.003013129
## Lag 4e+05                       0.02390704         0.000402376
## Lag 5e+05                       0.01065633         0.000788497
##           nodefactor.riskg.O4 nodefactor.riskg.Y2 nodefactor.riskg.Y3
## Lag 0            1.0000000000          1.00000000         1.000000000
## Lag 1e+05        0.0723691690          0.01429688        -0.009108107
## Lag 2e+05        0.0094687669          0.03680894         0.004120924
## Lag 3e+05        0.0001410807         -0.01637405        -0.022674064
## Lag 4e+05       -0.0237502286          0.01461509         0.008190934
## Lag 5e+05        0.0002956996         -0.01562636         0.003587994
##           nodefactor.race..wa.B nodefactor.race..wa.H nodefactor.region.EW
## Lag 0                1.00000000            1.00000000           1.00000000
## Lag 1e+05            0.18432689            0.25450913           0.10537383
## Lag 2e+05            0.09733650            0.13051342           0.05042974
## Lag 3e+05            0.05560339            0.07731362           0.05593624
## Lag 4e+05            0.04157838            0.05042004           0.01117125
## Lag 5e+05            0.03978150            0.04706249           0.01978982
##           nodefactor.region.OW nodematch.race..wa.B nodematch.race..wa.H
## Lag 0              1.000000000           1.00000000           1.00000000
## Lag 1e+05          0.090880752           0.22206856           0.34089213
## Lag 2e+05          0.039175692           0.09218435           0.19118613
## Lag 3e+05         -0.019713648           0.02313659           0.11184681
## Lag 4e+05         -0.005284444           0.03209245           0.07356146
## Lag 5e+05         -0.002237753           0.02429374           0.06347717
##           nodematch.race..wa.O absdiff.sqrt.age
## Lag 0              1.000000000       1.00000000
## Lag 1e+05          0.081568745       0.06187755
## Lag 2e+05          0.037379124       0.02533110
## Lag 3e+05          0.044235342       0.01408561
## Lag 4e+05         -0.001269057      -0.02246582
## Lag 5e+05          0.007526589      -0.01685211
## Chain 5 
##                  edges nodefactor.deg.main.deg.pers.0.1
## Lag 0      1.000000000                       1.00000000
## Lag 1e+05  0.141859336                       0.26323174
## Lag 2e+05  0.067572455                       0.11905219
## Lag 3e+05  0.024330710                       0.06236396
## Lag 4e+05  0.023038698                       0.04353498
## Lag 5e+05 -0.002550583                       0.03398363
##           nodefactor.deg.main.deg.pers.0.2
## Lag 0                          1.000000000
## Lag 1e+05                      0.020228218
## Lag 2e+05                      0.013309309
## Lag 3e+05                     -0.019394764
## Lag 4e+05                      0.001783148
## Lag 5e+05                     -0.019122919
##           nodefactor.deg.main.deg.pers.1.0
## Lag 0                         1.0000000000
## Lag 1e+05                    -0.0043788547
## Lag 2e+05                    -0.0333826931
## Lag 3e+05                     0.0237917936
## Lag 4e+05                     0.0206845054
## Lag 5e+05                     0.0004209339
##           nodefactor.deg.main.deg.pers.1.1
## Lag 0                           1.00000000
## Lag 1e+05                       0.21928280
## Lag 2e+05                       0.09243612
## Lag 3e+05                       0.06981057
## Lag 4e+05                       0.06043072
## Lag 5e+05                       0.01966646
##           nodefactor.deg.main.deg.pers.1.2 nodefactor.riskg.O3
## Lag 0                           1.00000000         1.000000000
## Lag 1e+05                       0.23958489         0.010345456
## Lag 2e+05                       0.12212418        -0.018950102
## Lag 3e+05                       0.07150297        -0.026391529
## Lag 4e+05                       0.03890681        -0.010305284
## Lag 5e+05                       0.03108642        -0.008526651
##           nodefactor.riskg.O4 nodefactor.riskg.Y2 nodefactor.riskg.Y3
## Lag 0             1.000000000         1.000000000        1.0000000000
## Lag 1e+05         0.071499222         0.006874296       -0.0086052387
## Lag 2e+05         0.067636438        -0.018231544       -0.0006179379
## Lag 3e+05         0.008193176         0.005819852       -0.0029209659
## Lag 4e+05        -0.030279549         0.018780463       -0.0030418251
## Lag 5e+05        -0.014652451         0.006202777       -0.0209453603
##           nodefactor.race..wa.B nodefactor.race..wa.H nodefactor.region.EW
## Lag 0               1.000000000            1.00000000          1.000000000
## Lag 1e+05           0.203399210            0.23509182          0.119166830
## Lag 2e+05           0.098170213            0.09172976          0.038646073
## Lag 3e+05           0.037626637            0.06050897          0.027034581
## Lag 4e+05           0.024157256            0.02815295          0.008692159
## Lag 5e+05           0.008478862            0.01713609          0.016708837
##           nodefactor.region.OW nodematch.race..wa.B nodematch.race..wa.H
## Lag 0              1.000000000          1.000000000           1.00000000
## Lag 1e+05          0.091360907          0.193397795           0.31265345
## Lag 2e+05          0.045196066          0.096833135           0.18173857
## Lag 3e+05          0.017781998          0.067078224           0.12464086
## Lag 4e+05          0.014631851          0.040215810           0.06180591
## Lag 5e+05         -0.009896387          0.009040489           0.07564116
##           nodematch.race..wa.O absdiff.sqrt.age
## Lag 0              1.000000000      1.000000000
## Lag 1e+05          0.094871119      0.056632284
## Lag 2e+05          0.052254132      0.006637746
## Lag 3e+05          0.001914888     -0.004746090
## Lag 4e+05          0.008480253      0.006960612
## Lag 5e+05         -0.028473151     -0.009671884
## Chain 6 
##                  edges nodefactor.deg.main.deg.pers.0.1
## Lag 0      1.000000000                       1.00000000
## Lag 1e+05  0.146429733                       0.21389817
## Lag 2e+05  0.050810896                       0.09438616
## Lag 3e+05  0.045309384                       0.06594349
## Lag 4e+05 -0.003960750                       0.01161823
## Lag 5e+05 -0.009377327                      -0.02446500
##           nodefactor.deg.main.deg.pers.0.2
## Lag 0                          1.000000000
## Lag 1e+05                      0.040174865
## Lag 2e+05                      0.010602099
## Lag 3e+05                      0.017583694
## Lag 4e+05                     -0.008827474
## Lag 5e+05                     -0.004536169
##           nodefactor.deg.main.deg.pers.1.0
## Lag 0                          1.000000000
## Lag 1e+05                      0.007024220
## Lag 2e+05                      0.005056349
## Lag 3e+05                      0.003087674
## Lag 4e+05                      0.012645121
## Lag 5e+05                     -0.008496157
##           nodefactor.deg.main.deg.pers.1.1
## Lag 0                          1.000000000
## Lag 1e+05                      0.251318843
## Lag 2e+05                      0.104792319
## Lag 3e+05                      0.050962205
## Lag 4e+05                      0.044092506
## Lag 5e+05                      0.007796539
##           nodefactor.deg.main.deg.pers.1.2 nodefactor.riskg.O3
## Lag 0                           1.00000000         1.000000000
## Lag 1e+05                       0.25749837        -0.005326010
## Lag 2e+05                       0.06841016         0.004883353
## Lag 3e+05                       0.06851989         0.022002242
## Lag 4e+05                       0.05096636        -0.010828733
## Lag 5e+05                       0.02573452         0.012247320
##           nodefactor.riskg.O4 nodefactor.riskg.Y2 nodefactor.riskg.Y3
## Lag 0            1.0000000000         1.000000000        1.0000000000
## Lag 1e+05        0.0523930200        -0.005850379        0.0105735196
## Lag 2e+05        0.0003982336         0.019825820       -0.0180092752
## Lag 3e+05       -0.0010659390        -0.005030450        0.0135792632
## Lag 4e+05        0.0062253160         0.014016531       -0.0079487735
## Lag 5e+05       -0.0296860952        -0.011752125        0.0006864114
##           nodefactor.race..wa.B nodefactor.race..wa.H nodefactor.region.EW
## Lag 0               1.000000000            1.00000000          1.000000000
## Lag 1e+05           0.162982608            0.24147591          0.140504310
## Lag 2e+05           0.059378500            0.10833951          0.023328230
## Lag 3e+05           0.069113369            0.05060211          0.010315607
## Lag 4e+05           0.019650846            0.07544432         -0.001837097
## Lag 5e+05          -0.004281127            0.02500527          0.004960597
##           nodefactor.region.OW nodematch.race..wa.B nodematch.race..wa.H
## Lag 0              1.000000000          1.000000000           1.00000000
## Lag 1e+05          0.102512323          0.174695171           0.33338311
## Lag 2e+05          0.004915070          0.055150142           0.20126168
## Lag 3e+05          0.039342429          0.035862367           0.14309675
## Lag 4e+05          0.006816913          0.009343012           0.10498882
## Lag 5e+05         -0.011874535         -0.017896606           0.06470738
##           nodematch.race..wa.O absdiff.sqrt.age
## Lag 0              1.000000000      1.000000000
## Lag 1e+05          0.114923581      0.049690588
## Lag 2e+05          0.038861994     -0.008758269
## Lag 3e+05          0.044013291      0.010777877
## Lag 4e+05          0.005822066     -0.016233649
## Lag 5e+05         -0.010136372     -0.042618501
## Chain 7 
##                  edges nodefactor.deg.main.deg.pers.0.1
## Lag 0      1.000000000                      1.000000000
## Lag 1e+05  0.118544244                      0.204508541
## Lag 2e+05  0.051881431                      0.089860929
## Lag 3e+05  0.001344600                      0.009537561
## Lag 4e+05  0.002276230                     -0.012591380
## Lag 5e+05 -0.008765857                     -0.019315805
##           nodefactor.deg.main.deg.pers.0.2
## Lag 0                          1.000000000
## Lag 1e+05                      0.034431567
## Lag 2e+05                      0.019497168
## Lag 3e+05                      0.002389839
## Lag 4e+05                      0.016819319
## Lag 5e+05                     -0.002945134
##           nodefactor.deg.main.deg.pers.1.0
## Lag 0                          1.000000000
## Lag 1e+05                      0.005068348
## Lag 2e+05                     -0.025865708
## Lag 3e+05                      0.018683161
## Lag 4e+05                      0.011147150
## Lag 5e+05                      0.008275449
##           nodefactor.deg.main.deg.pers.1.1
## Lag 0                          1.000000000
## Lag 1e+05                      0.262099486
## Lag 2e+05                      0.121572122
## Lag 3e+05                      0.036914817
## Lag 4e+05                      0.029432832
## Lag 5e+05                      0.007749906
##           nodefactor.deg.main.deg.pers.1.2 nodefactor.riskg.O3
## Lag 0                           1.00000000         1.000000000
## Lag 1e+05                       0.24698483         0.007646356
## Lag 2e+05                       0.11865524        -0.023077835
## Lag 3e+05                       0.06322231        -0.005040786
## Lag 4e+05                       0.01328459         0.022980081
## Lag 5e+05                       0.02860493        -0.028055940
##           nodefactor.riskg.O4 nodefactor.riskg.Y2 nodefactor.riskg.Y3
## Lag 0             1.000000000         1.000000000        1.0000000000
## Lag 1e+05         0.054048202        -0.021275686        0.0037736625
## Lag 2e+05         0.001448386        -0.007334797        0.0060893603
## Lag 3e+05         0.016148792         0.013863992        0.0007264019
## Lag 4e+05         0.023278631        -0.004325026        0.0008084412
## Lag 5e+05         0.034427930        -0.003479063       -0.0298294898
##           nodefactor.race..wa.B nodefactor.race..wa.H nodefactor.region.EW
## Lag 0               1.000000000            1.00000000          1.000000000
## Lag 1e+05           0.185890456            0.27040488          0.108635227
## Lag 2e+05           0.060141745            0.13245346          0.060688079
## Lag 3e+05           0.044191189            0.06017585          0.019598947
## Lag 4e+05           0.009742471            0.02264653          0.007237690
## Lag 5e+05          -0.008693382            0.00795050         -0.006669161
##           nodefactor.region.OW nodematch.race..wa.B nodematch.race..wa.H
## Lag 0              1.000000000           1.00000000           1.00000000
## Lag 1e+05          0.089878049           0.23045425           0.34811417
## Lag 2e+05          0.044402545           0.07018193           0.20377833
## Lag 3e+05          0.011334753           0.02135984           0.11541246
## Lag 4e+05          0.011893091           0.02118646           0.09368659
## Lag 5e+05         -0.001125065           0.03303309           0.04292301
##           nodematch.race..wa.O absdiff.sqrt.age
## Lag 0              1.000000000      1.000000000
## Lag 1e+05          0.076897547      0.060218666
## Lag 2e+05          0.049492194      0.054895383
## Lag 3e+05          0.005240154      0.016989139
## Lag 4e+05         -0.004469728      0.009819576
## Lag 5e+05         -0.019643179     -0.013556035
## Chain 8 
##                  edges nodefactor.deg.main.deg.pers.0.1
## Lag 0      1.000000000                      1.000000000
## Lag 1e+05  0.138268010                      0.239593281
## Lag 2e+05  0.022475924                      0.090380169
## Lag 3e+05  0.005308546                      0.039007136
## Lag 4e+05  0.004152257                      0.012277097
## Lag 5e+05 -0.011339317                      0.004044549
##           nodefactor.deg.main.deg.pers.0.2
## Lag 0                          1.000000000
## Lag 1e+05                      0.029697785
## Lag 2e+05                     -0.007892638
## Lag 3e+05                     -0.013161139
## Lag 4e+05                      0.007404809
## Lag 5e+05                     -0.007045731
##           nodefactor.deg.main.deg.pers.1.0
## Lag 0                          1.000000000
## Lag 1e+05                     -0.008459629
## Lag 2e+05                     -0.011793642
## Lag 3e+05                     -0.019359458
## Lag 4e+05                     -0.030523540
## Lag 5e+05                     -0.008880877
##           nodefactor.deg.main.deg.pers.1.1
## Lag 0                          1.000000000
## Lag 1e+05                      0.255165876
## Lag 2e+05                      0.096439385
## Lag 3e+05                      0.038479191
## Lag 4e+05                      0.021606743
## Lag 5e+05                      0.008956545
##           nodefactor.deg.main.deg.pers.1.2 nodefactor.riskg.O3
## Lag 0                         1.0000000000          1.00000000
## Lag 1e+05                     0.2196487109         -0.01476530
## Lag 2e+05                     0.1029871552          0.01485287
## Lag 3e+05                     0.0413873762         -0.03654493
## Lag 4e+05                     0.0101747952         -0.01544988
## Lag 5e+05                     0.0002585535          0.01454550
##           nodefactor.riskg.O4 nodefactor.riskg.Y2 nodefactor.riskg.Y3
## Lag 0             1.000000000        1.0000000000         1.000000000
## Lag 1e+05         0.074759885        0.0007311869        -0.009128602
## Lag 2e+05         0.004337738       -0.0056744860        -0.034254973
## Lag 3e+05         0.005329008        0.0050142215        -0.033812328
## Lag 4e+05         0.009358909       -0.0074458668        -0.018881387
## Lag 5e+05        -0.018330017        0.0173467308        -0.021313115
##           nodefactor.race..wa.B nodefactor.race..wa.H nodefactor.region.EW
## Lag 0                1.00000000            1.00000000          1.000000000
## Lag 1e+05            0.18002439            0.23346523          0.100910380
## Lag 2e+05            0.05251901            0.10796879          0.050405727
## Lag 3e+05            0.04830264            0.07019017          0.008068741
## Lag 4e+05            0.02252127            0.04636433          0.033788532
## Lag 5e+05            0.01100147            0.04440526          0.014610176
##           nodefactor.region.OW nodematch.race..wa.B nodematch.race..wa.H
## Lag 0              1.000000000           1.00000000           1.00000000
## Lag 1e+05          0.120743816           0.19881321           0.34260743
## Lag 2e+05          0.027371261           0.04461938           0.19848613
## Lag 3e+05          0.002833790           0.01776230           0.12927442
## Lag 4e+05         -0.005216131           0.02591556           0.08618060
## Lag 5e+05         -0.028888288          -0.01917405           0.03309567
##           nodematch.race..wa.O absdiff.sqrt.age
## Lag 0              1.000000000      1.000000000
## Lag 1e+05          0.103442317      0.090816966
## Lag 2e+05          0.018251543     -0.003436404
## Lag 3e+05          0.011405259      0.016722318
## Lag 4e+05          0.010480095     -0.001170132
## Lag 5e+05         -0.009874996      0.006648497
## 
## Sample statistics burn-in diagnostic (Geweke):
## Chain 8 
## 
## Fraction in 1st window = 0.1
## Fraction in 2nd window = 0.5 
## 
##                            edges nodefactor.deg.main.deg.pers.0.1 
##                         -1.00703                         -1.13846 
## nodefactor.deg.main.deg.pers.0.2 nodefactor.deg.main.deg.pers.1.0 
##                          1.94186                          0.15041 
## nodefactor.deg.main.deg.pers.1.1 nodefactor.deg.main.deg.pers.1.2 
##                         -0.01473                         -1.45567 
##              nodefactor.riskg.O3              nodefactor.riskg.O4 
##                         -0.89230                         -0.11357 
##              nodefactor.riskg.Y2              nodefactor.riskg.Y3 
##                          0.65680                         -0.48752 
##            nodefactor.race..wa.B            nodefactor.race..wa.H 
##                          1.23998                          0.08355 
##             nodefactor.region.EW             nodefactor.region.OW 
##                          0.85702                          0.56615 
##             nodematch.race..wa.B             nodematch.race..wa.H 
##                          3.04481                          0.35948 
##             nodematch.race..wa.O                 absdiff.sqrt.age 
##                         -1.82512                          0.02325 
## 
## Individual P-values (lower = worse):
##                            edges nodefactor.deg.main.deg.pers.0.1 
##                      0.313918345                      0.254928502 
## nodefactor.deg.main.deg.pers.0.2 nodefactor.deg.main.deg.pers.1.0 
##                      0.052154439                      0.880439423 
## nodefactor.deg.main.deg.pers.1.1 nodefactor.deg.main.deg.pers.1.2 
##                      0.988245157                      0.145484061 
##              nodefactor.riskg.O3              nodefactor.riskg.O4 
##                      0.372231237                      0.909578519 
##              nodefactor.riskg.Y2              nodefactor.riskg.Y3 
##                      0.511309510                      0.625891500 
##            nodefactor.race..wa.B            nodefactor.race..wa.H 
##                      0.214984151                      0.933417308 
##             nodefactor.region.EW             nodefactor.region.OW 
##                      0.391432115                      0.571290263 
##             nodematch.race..wa.B             nodematch.race..wa.H 
##                      0.002328263                      0.719236807 
##             nodematch.race..wa.O                 absdiff.sqrt.age 
##                      0.067982409                      0.981450945 
## Joint P-value (lower = worse):  7.032381e-05 .
## Chain 8 
## 
## Fraction in 1st window = 0.1
## Fraction in 2nd window = 0.5 
## 
##                            edges nodefactor.deg.main.deg.pers.0.1 
##                          2.21347                          1.16938 
## nodefactor.deg.main.deg.pers.0.2 nodefactor.deg.main.deg.pers.1.0 
##                          0.78280                         -1.11909 
## nodefactor.deg.main.deg.pers.1.1 nodefactor.deg.main.deg.pers.1.2 
##                          1.58766                          1.66901 
##              nodefactor.riskg.O3              nodefactor.riskg.O4 
##                         -1.15736                          2.06348 
##              nodefactor.riskg.Y2              nodefactor.riskg.Y3 
##                         -0.58553                          0.01410 
##            nodefactor.race..wa.B            nodefactor.race..wa.H 
##                         -0.13437                          2.81408 
##             nodefactor.region.EW             nodefactor.region.OW 
##                          0.73337                          1.50376 
##             nodematch.race..wa.B             nodematch.race..wa.H 
##                         -0.04712                          1.14374 
##             nodematch.race..wa.O                 absdiff.sqrt.age 
##                          0.97446                          1.60000 
## 
## Individual P-values (lower = worse):
##                            edges nodefactor.deg.main.deg.pers.0.1 
##                      0.026864947                      0.242250308 
## nodefactor.deg.main.deg.pers.0.2 nodefactor.deg.main.deg.pers.1.0 
##                      0.433744103                      0.263099952 
## nodefactor.deg.main.deg.pers.1.1 nodefactor.deg.main.deg.pers.1.2 
##                      0.112364047                      0.095115411 
##              nodefactor.riskg.O3              nodefactor.riskg.O4 
##                      0.247125155                      0.039066679 
##              nodefactor.riskg.Y2              nodefactor.riskg.Y3 
##                      0.558192190                      0.988748752 
##            nodefactor.race..wa.B            nodefactor.race..wa.H 
##                      0.893111603                      0.004891726 
##             nodefactor.region.EW             nodefactor.region.OW 
##                      0.463335031                      0.132641983 
##             nodematch.race..wa.B             nodematch.race..wa.H 
##                      0.962414630                      0.252729578 
##             nodematch.race..wa.O                 absdiff.sqrt.age 
##                      0.329825996                      0.109598646 
## Joint P-value (lower = worse):  0.9971656 .
## Chain 8 
## 
## Fraction in 1st window = 0.1
## Fraction in 2nd window = 0.5 
## 
##                            edges nodefactor.deg.main.deg.pers.0.1 
##                          0.98852                          0.03427 
## nodefactor.deg.main.deg.pers.0.2 nodefactor.deg.main.deg.pers.1.0 
##                          0.17830                          0.14459 
## nodefactor.deg.main.deg.pers.1.1 nodefactor.deg.main.deg.pers.1.2 
##                         -0.35357                          2.16301 
##              nodefactor.riskg.O3              nodefactor.riskg.O4 
##                          0.37124                          1.78618 
##              nodefactor.riskg.Y2              nodefactor.riskg.Y3 
##                         -1.50018                          1.27575 
##            nodefactor.race..wa.B            nodefactor.race..wa.H 
##                         -0.25483                          0.21451 
##             nodefactor.region.EW             nodefactor.region.OW 
##                         -0.51555                          0.67525 
##             nodematch.race..wa.B             nodematch.race..wa.H 
##                          1.70638                         -0.32444 
##             nodematch.race..wa.O                 absdiff.sqrt.age 
##                          1.03737                          1.37129 
## 
## Individual P-values (lower = worse):
##                            edges nodefactor.deg.main.deg.pers.0.1 
##                       0.32289866                       0.97265880 
## nodefactor.deg.main.deg.pers.0.2 nodefactor.deg.main.deg.pers.1.0 
##                       0.85848808                       0.88503491 
## nodefactor.deg.main.deg.pers.1.1 nodefactor.deg.main.deg.pers.1.2 
##                       0.72366164                       0.03054016 
##              nodefactor.riskg.O3              nodefactor.riskg.O4 
##                       0.71046154                       0.07407081 
##              nodefactor.riskg.Y2              nodefactor.riskg.Y3 
##                       0.13356773                       0.20204297 
##            nodefactor.race..wa.B            nodefactor.race..wa.H 
##                       0.79885727                       0.83014858 
##             nodefactor.region.EW             nodefactor.region.OW 
##                       0.60617017                       0.49951414 
##             nodematch.race..wa.B             nodematch.race..wa.H 
##                       0.08793687                       0.74560763 
##             nodematch.race..wa.O                 absdiff.sqrt.age 
##                       0.29956179                       0.17028567 
## Joint P-value (lower = worse):  0.1853672 .
## Chain 8 
## 
## Fraction in 1st window = 0.1
## Fraction in 2nd window = 0.5 
## 
##                            edges nodefactor.deg.main.deg.pers.0.1 
##                         -0.85872                         -0.87987 
## nodefactor.deg.main.deg.pers.0.2 nodefactor.deg.main.deg.pers.1.0 
##                          0.36650                          0.52669 
## nodefactor.deg.main.deg.pers.1.1 nodefactor.deg.main.deg.pers.1.2 
##                         -0.14199                         -1.66318 
##              nodefactor.riskg.O3              nodefactor.riskg.O4 
##                         -0.16610                         -0.82847 
##              nodefactor.riskg.Y2              nodefactor.riskg.Y3 
##                          1.17896                         -0.01855 
##            nodefactor.race..wa.B            nodefactor.race..wa.H 
##                          0.46441                         -0.30425 
##             nodefactor.region.EW             nodefactor.region.OW 
##                          0.83459                         -0.94426 
##             nodematch.race..wa.B             nodematch.race..wa.H 
##                         -1.63266                          0.25031 
##             nodematch.race..wa.O                 absdiff.sqrt.age 
##                         -0.17568                         -0.14602 
## 
## Individual P-values (lower = worse):
##                            edges nodefactor.deg.main.deg.pers.0.1 
##                       0.39049258                       0.37893188 
## nodefactor.deg.main.deg.pers.0.2 nodefactor.deg.main.deg.pers.1.0 
##                       0.71398851                       0.59840886 
## nodefactor.deg.main.deg.pers.1.1 nodefactor.deg.main.deg.pers.1.2 
##                       0.88708917                       0.09627569 
##              nodefactor.riskg.O3              nodefactor.riskg.O4 
##                       0.86807669                       0.40740503 
##              nodefactor.riskg.Y2              nodefactor.riskg.Y3 
##                       0.23841455                       0.98519772 
##            nodefactor.race..wa.B            nodefactor.race..wa.H 
##                       0.64235553                       0.76093607 
##             nodefactor.region.EW             nodefactor.region.OW 
##                       0.40394759                       0.34503561 
##             nodematch.race..wa.B             nodematch.race..wa.H 
##                       0.10254045                       0.80235010 
##             nodematch.race..wa.O                 absdiff.sqrt.age 
##                       0.86054487                       0.88390664 
## Joint P-value (lower = worse):  5.793033e-34 .
## Chain 8 
## 
## Fraction in 1st window = 0.1
## Fraction in 2nd window = 0.5 
## 
##                            edges nodefactor.deg.main.deg.pers.0.1 
##                         -1.33547                         -2.04257 
## nodefactor.deg.main.deg.pers.0.2 nodefactor.deg.main.deg.pers.1.0 
##                          0.53342                          0.26897 
## nodefactor.deg.main.deg.pers.1.1 nodefactor.deg.main.deg.pers.1.2 
##                         -2.12001                          1.81244 
##              nodefactor.riskg.O3              nodefactor.riskg.O4 
##                         -1.77704                         -0.94025 
##              nodefactor.riskg.Y2              nodefactor.riskg.Y3 
##                         -0.07102                          0.21282 
##            nodefactor.race..wa.B            nodefactor.race..wa.H 
##                         -2.29543                         -2.34880 
##             nodefactor.region.EW             nodefactor.region.OW 
##                         -1.15958                         -1.31951 
##             nodematch.race..wa.B             nodematch.race..wa.H 
##                         -1.73288                         -1.57003 
##             nodematch.race..wa.O                 absdiff.sqrt.age 
##                          0.63060                         -1.23131 
## 
## Individual P-values (lower = worse):
##                            edges nodefactor.deg.main.deg.pers.0.1 
##                       0.18172297                       0.04109456 
## nodefactor.deg.main.deg.pers.0.2 nodefactor.deg.main.deg.pers.1.0 
##                       0.59374227                       0.78795394 
## nodefactor.deg.main.deg.pers.1.1 nodefactor.deg.main.deg.pers.1.2 
##                       0.03400560                       0.06991805 
##              nodefactor.riskg.O3              nodefactor.riskg.O4 
##                       0.07556239                       0.34708909 
##              nodefactor.riskg.Y2              nodefactor.riskg.Y3 
##                       0.94338141                       0.83146861 
##            nodefactor.race..wa.B            nodefactor.race..wa.H 
##                       0.02170832                       0.01883409 
##             nodefactor.region.EW             nodefactor.region.OW 
##                       0.24622157                       0.18699996 
##             nodematch.race..wa.B             nodematch.race..wa.H 
##                       0.08311783                       0.11640725 
##             nodematch.race..wa.O                 absdiff.sqrt.age 
##                       0.52829947                       0.21820755 
## Joint P-value (lower = worse):  0.009573772 .
## Chain 8 
## 
## Fraction in 1st window = 0.1
## Fraction in 2nd window = 0.5 
## 
##                            edges nodefactor.deg.main.deg.pers.0.1 
##                         -0.44769                         -0.86900 
## nodefactor.deg.main.deg.pers.0.2 nodefactor.deg.main.deg.pers.1.0 
##                         -0.45620                          0.98582 
## nodefactor.deg.main.deg.pers.1.1 nodefactor.deg.main.deg.pers.1.2 
##                         -0.07921                         -0.48160 
##              nodefactor.riskg.O3              nodefactor.riskg.O4 
##                         -1.50487                         -1.56308 
##              nodefactor.riskg.Y2              nodefactor.riskg.Y3 
##                         -0.03429                          0.02936 
##            nodefactor.race..wa.B            nodefactor.race..wa.H 
##                         -1.94566                         -1.89733 
##             nodefactor.region.EW             nodefactor.region.OW 
##                          0.09207                         -1.18132 
##             nodematch.race..wa.B             nodematch.race..wa.H 
##                         -0.85663                         -2.74072 
##             nodematch.race..wa.O                 absdiff.sqrt.age 
##                          0.68024                         -0.09961 
## 
## Individual P-values (lower = worse):
##                            edges nodefactor.deg.main.deg.pers.0.1 
##                      0.654375600                      0.384849446 
## nodefactor.deg.main.deg.pers.0.2 nodefactor.deg.main.deg.pers.1.0 
##                      0.648249712                      0.324220565 
## nodefactor.deg.main.deg.pers.1.1 nodefactor.deg.main.deg.pers.1.2 
##                      0.936867989                      0.630090902 
##              nodefactor.riskg.O3              nodefactor.riskg.O4 
##                      0.132357431                      0.118033113 
##              nodefactor.riskg.Y2              nodefactor.riskg.Y3 
##                      0.972648073                      0.976574736 
##            nodefactor.race..wa.B            nodefactor.race..wa.H 
##                      0.051695786                      0.057784673 
##             nodefactor.region.EW             nodefactor.region.OW 
##                      0.926639275                      0.237475345 
##             nodematch.race..wa.B             nodematch.race..wa.H 
##                      0.391649683                      0.006130532 
##             nodematch.race..wa.O                 absdiff.sqrt.age 
##                      0.496353263                      0.920652530 
## Joint P-value (lower = worse):  1 .
## Chain 8 
## 
## Fraction in 1st window = 0.1
## Fraction in 2nd window = 0.5 
## 
##                            edges nodefactor.deg.main.deg.pers.0.1 
##                         -1.76903                         -0.88626 
## nodefactor.deg.main.deg.pers.0.2 nodefactor.deg.main.deg.pers.1.0 
##                         -1.03079                         -0.49953 
## nodefactor.deg.main.deg.pers.1.1 nodefactor.deg.main.deg.pers.1.2 
##                         -0.04141                         -0.78590 
##              nodefactor.riskg.O3              nodefactor.riskg.O4 
##                         -0.26974                         -1.51307 
##              nodefactor.riskg.Y2              nodefactor.riskg.Y3 
##                         -0.41882                         -1.10155 
##            nodefactor.race..wa.B            nodefactor.race..wa.H 
##                          0.02943                         -1.21911 
##             nodefactor.region.EW             nodefactor.region.OW 
##                          0.02914                         -0.82736 
##             nodematch.race..wa.B             nodematch.race..wa.H 
##                         -0.01330                         -1.37732 
##             nodematch.race..wa.O                 absdiff.sqrt.age 
##                         -1.48806                         -2.72102 
## 
## Individual P-values (lower = worse):
##                            edges nodefactor.deg.main.deg.pers.0.1 
##                      0.076889028                      0.375474956 
## nodefactor.deg.main.deg.pers.0.2 nodefactor.deg.main.deg.pers.1.0 
##                      0.302637339                      0.617405988 
## nodefactor.deg.main.deg.pers.1.1 nodefactor.deg.main.deg.pers.1.2 
##                      0.966971986                      0.431927180 
##              nodefactor.riskg.O3              nodefactor.riskg.O4 
##                      0.787358332                      0.130262286 
##              nodefactor.riskg.Y2              nodefactor.riskg.Y3 
##                      0.675349104                      0.270656008 
##            nodefactor.race..wa.B            nodefactor.race..wa.H 
##                      0.976519523                      0.222803030 
##             nodefactor.region.EW             nodefactor.region.OW 
##                      0.976754899                      0.408034735 
##             nodematch.race..wa.B             nodematch.race..wa.H 
##                      0.989388743                      0.168412849 
##             nodematch.race..wa.O                 absdiff.sqrt.age 
##                      0.136734753                      0.006508127 
## Joint P-value (lower = worse):  1 .
## Chain 8 
## 
## Fraction in 1st window = 0.1
## Fraction in 2nd window = 0.5 
## 
##                            edges nodefactor.deg.main.deg.pers.0.1 
##                         0.002238                         1.202013 
## nodefactor.deg.main.deg.pers.0.2 nodefactor.deg.main.deg.pers.1.0 
##                        -0.873707                         0.271300 
## nodefactor.deg.main.deg.pers.1.1 nodefactor.deg.main.deg.pers.1.2 
##                         0.245436                        -0.265179 
##              nodefactor.riskg.O3              nodefactor.riskg.O4 
##                        -1.134466                        -0.219949 
##              nodefactor.riskg.Y2              nodefactor.riskg.Y3 
##                        -0.503565                         1.693236 
##            nodefactor.race..wa.B            nodefactor.race..wa.H 
##                         1.408517                        -0.953453 
##             nodefactor.region.EW             nodefactor.region.OW 
##                         0.976078                        -0.936797 
##             nodematch.race..wa.B             nodematch.race..wa.H 
##                         0.405580                        -0.429576 
##             nodematch.race..wa.O                 absdiff.sqrt.age 
##                         0.048991                         0.650336 
## 
## Individual P-values (lower = worse):
##                            edges nodefactor.deg.main.deg.pers.0.1 
##                       0.99821438                       0.22935845 
## nodefactor.deg.main.deg.pers.0.2 nodefactor.deg.main.deg.pers.1.0 
##                       0.38227764                       0.78615993 
## nodefactor.deg.main.deg.pers.1.1 nodefactor.deg.main.deg.pers.1.2 
##                       0.80611860                       0.79087128 
##              nodefactor.riskg.O3              nodefactor.riskg.O4 
##                       0.25659924                       0.82591098 
##              nodefactor.riskg.Y2              nodefactor.riskg.Y3 
##                       0.61456728                       0.09041063 
##            nodefactor.race..wa.B            nodefactor.race..wa.H 
##                       0.15897815                       0.34036083 
##             nodefactor.region.EW             nodefactor.region.OW 
##                       0.32902570                       0.34886295 
##             nodematch.race..wa.B             nodematch.race..wa.H 
##                       0.68505158                       0.66750409 
##             nodematch.race..wa.O                 absdiff.sqrt.age 
##                       0.96092638                       0.51547547 
## Joint P-value (lower = worse):  0.9840542 .
## Warning in formals(fun): argument is not a function

## 
## MCMC diagnostics shown here are from the last round of simulation, prior to computation of final parameter estimates. Because the final estimates are refinements of those used for this simulation run, these diagnostics may understate model performance. To directly assess the performance of the final model on in-model statistics, please use the GOF command: gof(ergmFitObject, GOF=~model).

Model 8

## Sample statistics summary:
## 
## Iterations = 1e+06:375900000
## Thinning interval = 1e+05 
## Number of chains = 8 
## Sample size per chain = 3750 
## 
## 1. Empirical mean and standard deviation for each variable,
##    plus standard error of the mean:
## 
##                                     Mean     SD Naive SE Time-series SE
## edges                             3.1536 21.895  0.12641        0.16943
## nodefactor.deg.main.deg.pers.0.1  1.2120 14.221  0.08211        0.12994
## nodefactor.deg.main.deg.pers.0.2  0.5271  6.218  0.03590        0.03783
## nodefactor.deg.main.deg.pers.1.0  0.2732  6.333  0.03657        0.03652
## nodefactor.deg.main.deg.pers.1.1  0.4973 12.387  0.07152        0.11614
## nodefactor.deg.main.deg.pers.1.2  0.5981 12.979  0.07494        0.11871
## nodefactor.riskg.O3               0.1885  2.689  0.01553        0.01557
## nodefactor.riskg.O4               1.1292 11.754  0.06786        0.08113
## nodefactor.riskg.Y2              -0.1241  2.850  0.01646        0.01652
## nodefactor.riskg.Y3               0.3195  8.771  0.05064        0.05149
## nodefactor.race..wa.B             2.5947  9.256  0.05344        0.07808
## nodefactor.race..wa.H             1.3192 13.263  0.07657        0.13088
## nodefactor.region.EW              0.6758 11.288  0.06517        0.12279
## nodefactor.region.OW              0.6762 20.417  0.11788        0.15530
## nodematch.race..wa.B              1.4928  1.997  0.01153        0.01853
## nodematch.race..wa.H              0.3585  3.689  0.02130        0.04467
## nodematch.race..wa.O              0.8681 16.942  0.09782        0.12643
## nodematch.region                  2.9910 19.687  0.11367        0.15961
## absdiff.sqrt.age                  2.8393 22.476  0.12976        0.14917
## 
## 2. Quantiles for each variable:
## 
##                                     2.5%      25%      50%    75%  97.5%
## edges                            -39.159 -12.1586  2.84138 17.841 46.841
## nodefactor.deg.main.deg.pers.0.1 -26.310  -8.3100  0.68996 10.690 29.690
## nodefactor.deg.main.deg.pers.0.2 -11.371  -3.3710  0.62897  4.629 13.629
## nodefactor.deg.main.deg.pers.1.0 -12.033  -4.0335 -0.03347  3.967 12.967
## nodefactor.deg.main.deg.pers.1.1 -22.538  -7.5379  0.46214  8.462 25.462
## nodefactor.deg.main.deg.pers.1.2 -24.388  -8.3881  0.61188  9.612 26.612
## nodefactor.riskg.O3               -4.856  -1.8558  0.14418  2.144  6.144
## nodefactor.riskg.O4              -21.513  -6.5127  0.48734  8.487 24.487
## nodefactor.riskg.Y2               -5.202  -2.2024 -0.20238  1.798  5.798
## nodefactor.riskg.Y3              -15.786  -5.7860  0.21403  6.214 18.214
## nodefactor.race..wa.B            -15.591  -3.5908  2.40918  8.409 21.409
## nodefactor.race..wa.H            -24.174  -8.1739  0.82608  9.826 27.826
## nodefactor.region.EW             -20.501  -7.5014  0.49862  8.499 23.499
## nodefactor.region.OW             -38.486 -13.4862  0.51379 14.514 41.514
## nodematch.race..wa.B              -1.540   0.4601  1.46015  2.460  5.460
## nodematch.race..wa.H              -6.269  -2.2690 -0.26902  2.731  7.731
## nodematch.race..wa.O             -31.880 -10.8800  1.11998 12.120 35.120
## nodematch.region                 -35.327 -10.3269  2.67310 16.673 42.673
## absdiff.sqrt.age                 -40.241 -12.4725  2.44631 17.751 48.225
## 
## 
## Sample statistics cross-correlations:
##                                       edges
## edges                            1.00000000
## nodefactor.deg.main.deg.pers.0.1 0.55370244
## nodefactor.deg.main.deg.pers.0.2 0.27156284
## nodefactor.deg.main.deg.pers.1.0 0.27013977
## nodefactor.deg.main.deg.pers.1.1 0.49994536
## nodefactor.deg.main.deg.pers.1.2 0.51075457
## nodefactor.riskg.O3              0.12100448
## nodefactor.riskg.O4              0.42831958
## nodefactor.riskg.Y2              0.12295394
## nodefactor.riskg.Y3              0.36880468
## nodefactor.race..wa.B            0.38323017
## nodefactor.race..wa.H            0.51061101
## nodefactor.region.EW             0.33899606
## nodefactor.region.OW             0.54804058
## nodematch.race..wa.B             0.09331197
## nodematch.race..wa.H             0.16845344
## nodematch.race..wa.O             0.77361592
## nodematch.region                 0.89506007
## absdiff.sqrt.age                 0.77321735
##                                  nodefactor.deg.main.deg.pers.0.1
## edges                                                  0.55370244
## nodefactor.deg.main.deg.pers.0.1                       1.00000000
## nodefactor.deg.main.deg.pers.0.2                       0.08056047
## nodefactor.deg.main.deg.pers.1.0                       0.06937749
## nodefactor.deg.main.deg.pers.1.1                       0.15298314
## nodefactor.deg.main.deg.pers.1.2                       0.14180555
## nodefactor.riskg.O3                                    0.07007030
## nodefactor.riskg.O4                                    0.23796555
## nodefactor.riskg.Y2                                    0.06534959
## nodefactor.riskg.Y3                                    0.18738423
## nodefactor.race..wa.B                                  0.23851586
## nodefactor.race..wa.H                                  0.20524282
## nodefactor.region.EW                                   0.17774931
## nodefactor.region.OW                                   0.35231048
## nodematch.race..wa.B                                   0.06115229
## nodematch.race..wa.H                                   0.04072498
## nodematch.race..wa.O                                   0.46151575
## nodematch.region                                       0.48990203
## absdiff.sqrt.age                                       0.41842794
##                                  nodefactor.deg.main.deg.pers.0.2
## edges                                                  0.27156284
## nodefactor.deg.main.deg.pers.0.1                       0.08056047
## nodefactor.deg.main.deg.pers.0.2                       1.00000000
## nodefactor.deg.main.deg.pers.1.0                       0.03591671
## nodefactor.deg.main.deg.pers.1.1                       0.06071575
## nodefactor.deg.main.deg.pers.1.2                       0.07556606
## nodefactor.riskg.O3                                    0.03815016
## nodefactor.riskg.O4                                    0.12740122
## nodefactor.riskg.Y2                                    0.03138381
## nodefactor.riskg.Y3                                    0.10872152
## nodefactor.race..wa.B                                  0.11933379
## nodefactor.race..wa.H                                  0.14140374
## nodefactor.region.EW                                   0.07112511
## nodefactor.region.OW                                   0.14283431
## nodematch.race..wa.B                                   0.02271257
## nodematch.race..wa.H                                   0.04479195
## nodematch.race..wa.O                                   0.20131042
## nodematch.region                                       0.25042027
## absdiff.sqrt.age                                       0.21046671
##                                  nodefactor.deg.main.deg.pers.1.0
## edges                                                  0.27013977
## nodefactor.deg.main.deg.pers.0.1                       0.06937749
## nodefactor.deg.main.deg.pers.0.2                       0.03591671
## nodefactor.deg.main.deg.pers.1.0                       1.00000000
## nodefactor.deg.main.deg.pers.1.1                       0.05744992
## nodefactor.deg.main.deg.pers.1.2                       0.06919164
## nodefactor.riskg.O3                                    0.01991066
## nodefactor.riskg.O4                                    0.11233279
## nodefactor.riskg.Y2                                    0.04010717
## nodefactor.riskg.Y3                                    0.09072432
## nodefactor.race..wa.B                                  0.09695218
## nodefactor.race..wa.H                                  0.16952089
## nodefactor.region.EW                                   0.10947877
## nodefactor.region.OW                                   0.14867228
## nodematch.race..wa.B                                   0.02600118
## nodematch.race..wa.H                                   0.06323372
## nodematch.race..wa.O                                   0.19288659
## nodematch.region                                       0.23763000
## absdiff.sqrt.age                                       0.20676726
##                                  nodefactor.deg.main.deg.pers.1.1
## edges                                                  0.49994536
## nodefactor.deg.main.deg.pers.0.1                       0.15298314
## nodefactor.deg.main.deg.pers.0.2                       0.06071575
## nodefactor.deg.main.deg.pers.1.0                       0.05744992
## nodefactor.deg.main.deg.pers.1.1                       1.00000000
## nodefactor.deg.main.deg.pers.1.2                       0.13071195
## nodefactor.riskg.O3                                    0.06077506
## nodefactor.riskg.O4                                    0.19192832
## nodefactor.riskg.Y2                                    0.06395472
## nodefactor.riskg.Y3                                    0.18867308
## nodefactor.race..wa.B                                  0.18118749
## nodefactor.race..wa.H                                  0.30039627
## nodefactor.region.EW                                   0.15432897
## nodefactor.region.OW                                   0.28144497
## nodematch.race..wa.B                                   0.04403783
## nodematch.race..wa.H                                   0.11713878
## nodematch.race..wa.O                                   0.36651092
## nodematch.region                                       0.45201198
## absdiff.sqrt.age                                       0.37786817
##                                  nodefactor.deg.main.deg.pers.1.2
## edges                                                  0.51075457
## nodefactor.deg.main.deg.pers.0.1                       0.14180555
## nodefactor.deg.main.deg.pers.0.2                       0.07556606
## nodefactor.deg.main.deg.pers.1.0                       0.06919164
## nodefactor.deg.main.deg.pers.1.1                       0.13071195
## nodefactor.deg.main.deg.pers.1.2                       1.00000000
## nodefactor.riskg.O3                                    0.06875248
## nodefactor.riskg.O4                                    0.21244589
## nodefactor.riskg.Y2                                    0.06436779
## nodefactor.riskg.Y3                                    0.19292938
## nodefactor.race..wa.B                                  0.13174330
## nodefactor.race..wa.H                                  0.32581196
## nodefactor.region.EW                                   0.20977002
## nodefactor.region.OW                                   0.24647164
## nodematch.race..wa.B                                   0.02045403
## nodematch.race..wa.H                                   0.13568023
## nodematch.race..wa.O                                   0.38456028
## nodematch.region                                       0.45738353
## absdiff.sqrt.age                                       0.39946393
##                                  nodefactor.riskg.O3 nodefactor.riskg.O4
## edges                                    0.121004484          0.42831958
## nodefactor.deg.main.deg.pers.0.1         0.070070297          0.23796555
## nodefactor.deg.main.deg.pers.0.2         0.038150156          0.12740122
## nodefactor.deg.main.deg.pers.1.0         0.019910664          0.11233279
## nodefactor.deg.main.deg.pers.1.1         0.060775058          0.19192832
## nodefactor.deg.main.deg.pers.1.2         0.068752484          0.21244589
## nodefactor.riskg.O3                      1.000000000          0.05678409
## nodefactor.riskg.O4                      0.056784087          1.00000000
## nodefactor.riskg.Y2                      0.007949908          0.02951831
## nodefactor.riskg.Y3                      0.018030116          0.07407588
## nodefactor.race..wa.B                    0.027112596          0.18471979
## nodefactor.race..wa.H                    0.059875601          0.27707882
## nodefactor.region.EW                     0.041155839          0.14391569
## nodefactor.region.OW                     0.065278783          0.23007425
## nodematch.race..wa.B                     0.006652550          0.04774873
## nodematch.race..wa.H                     0.022496505          0.10994369
## nodematch.race..wa.O                     0.103780265          0.28898179
## nodematch.region                         0.109452692          0.38575122
## absdiff.sqrt.age                         0.117851021          0.43421744
##                                  nodefactor.riskg.Y2 nodefactor.riskg.Y3
## edges                                    0.122953943         0.368804681
## nodefactor.deg.main.deg.pers.0.1         0.065349589         0.187384227
## nodefactor.deg.main.deg.pers.0.2         0.031383812         0.108721520
## nodefactor.deg.main.deg.pers.1.0         0.040107166         0.090724322
## nodefactor.deg.main.deg.pers.1.1         0.063954716         0.188673078
## nodefactor.deg.main.deg.pers.1.2         0.064367785         0.192929378
## nodefactor.riskg.O3                      0.007949908         0.018030116
## nodefactor.riskg.O4                      0.029518313         0.074075880
## nodefactor.riskg.Y2                      1.000000000         0.008122821
## nodefactor.riskg.Y3                      0.008122821         1.000000000
## nodefactor.race..wa.B                    0.049726484         0.138257148
## nodefactor.race..wa.H                    0.067708750         0.188283754
## nodefactor.region.EW                     0.041707933         0.114638365
## nodefactor.region.OW                     0.064409962         0.194462747
## nodematch.race..wa.B                     0.014013461         0.036481957
## nodematch.race..wa.H                     0.024584362         0.063627350
## nodematch.race..wa.O                     0.091365669         0.287770196
## nodematch.region                         0.111649132         0.337661029
## absdiff.sqrt.age                         0.092765202         0.275136890
##                                  nodefactor.race..wa.B
## edges                                     0.3832301677
## nodefactor.deg.main.deg.pers.0.1          0.2385158559
## nodefactor.deg.main.deg.pers.0.2          0.1193337903
## nodefactor.deg.main.deg.pers.1.0          0.0969521797
## nodefactor.deg.main.deg.pers.1.1          0.1811874947
## nodefactor.deg.main.deg.pers.1.2          0.1317433018
## nodefactor.riskg.O3                       0.0271125961
## nodefactor.riskg.O4                       0.1847197851
## nodefactor.riskg.Y2                       0.0497264845
## nodefactor.riskg.Y3                       0.1382571478
## nodefactor.race..wa.B                     1.0000000000
## nodefactor.race..wa.H                     0.1315735461
## nodefactor.region.EW                      0.0752231545
## nodefactor.region.OW                      0.1311124409
## nodematch.race..wa.B                      0.4348823200
## nodematch.race..wa.H                      0.0026206719
## nodematch.race..wa.O                      0.0007773791
## nodematch.region                          0.3531366888
## absdiff.sqrt.age                          0.3026103987
##                                  nodefactor.race..wa.H
## edges                                     0.5106110135
## nodefactor.deg.main.deg.pers.0.1          0.2052428185
## nodefactor.deg.main.deg.pers.0.2          0.1414037418
## nodefactor.deg.main.deg.pers.1.0          0.1695208937
## nodefactor.deg.main.deg.pers.1.1          0.3003962719
## nodefactor.deg.main.deg.pers.1.2          0.3258119627
## nodefactor.riskg.O3                       0.0598756008
## nodefactor.riskg.O4                       0.2770788168
## nodefactor.riskg.Y2                       0.0677087495
## nodefactor.riskg.Y3                       0.1882837540
## nodefactor.race..wa.B                     0.1315735461
## nodefactor.race..wa.H                     1.0000000000
## nodefactor.region.EW                      0.2889544439
## nodefactor.region.OW                      0.2331999444
## nodematch.race..wa.B                     -0.0006844696
## nodematch.race..wa.H                      0.5541746344
## nodematch.race..wa.O                     -0.0011505123
## nodematch.region                          0.4459691645
## absdiff.sqrt.age                          0.4039554065
##                                  nodefactor.region.EW nodefactor.region.OW
## edges                                      0.33899606           0.54804058
## nodefactor.deg.main.deg.pers.0.1           0.17774931           0.35231048
## nodefactor.deg.main.deg.pers.0.2           0.07112511           0.14283431
## nodefactor.deg.main.deg.pers.1.0           0.10947877           0.14867228
## nodefactor.deg.main.deg.pers.1.1           0.15432897           0.28144497
## nodefactor.deg.main.deg.pers.1.2           0.20977002           0.24647164
## nodefactor.riskg.O3                        0.04115584           0.06527878
## nodefactor.riskg.O4                        0.14391569           0.23007425
## nodefactor.riskg.Y2                        0.04170793           0.06440996
## nodefactor.riskg.Y3                        0.11463837           0.19446275
## nodefactor.race..wa.B                      0.07522315           0.13111244
## nodefactor.race..wa.H                      0.28895444           0.23319994
## nodefactor.region.EW                       1.00000000           0.06401049
## nodefactor.region.OW                       0.06401049           1.00000000
## nodematch.race..wa.B                       0.01493065           0.00763674
## nodematch.race..wa.H                       0.14274282           0.06444802
## nodematch.race..wa.O                       0.21803140           0.48118974
## nodematch.region                           0.18849645           0.43755963
## absdiff.sqrt.age                           0.25837813           0.42084015
##                                  nodematch.race..wa.B nodematch.race..wa.H
## edges                                    0.0933119668          0.168453442
## nodefactor.deg.main.deg.pers.0.1         0.0611522941          0.040724976
## nodefactor.deg.main.deg.pers.0.2         0.0227125716          0.044791953
## nodefactor.deg.main.deg.pers.1.0         0.0260011765          0.063233717
## nodefactor.deg.main.deg.pers.1.1         0.0440378250          0.117138783
## nodefactor.deg.main.deg.pers.1.2         0.0204540334          0.135680234
## nodefactor.riskg.O3                      0.0066525503          0.022496505
## nodefactor.riskg.O4                      0.0477487322          0.109943692
## nodefactor.riskg.Y2                      0.0140134606          0.024584362
## nodefactor.riskg.Y3                      0.0364819567          0.063627350
## nodefactor.race..wa.B                    0.4348823200          0.002620672
## nodefactor.race..wa.H                   -0.0006844696          0.554174634
## nodefactor.region.EW                     0.0149306507          0.142742818
## nodefactor.region.OW                     0.0076367402          0.064448018
## nodematch.race..wa.B                     1.0000000000          0.002862252
## nodematch.race..wa.H                     0.0028622516          1.000000000
## nodematch.race..wa.O                     0.0014841620          0.001376098
## nodematch.region                         0.0889099625          0.147582074
## absdiff.sqrt.age                         0.0747830746          0.132406205
##                                  nodematch.race..wa.O nodematch.region
## edges                                    0.7736159246       0.89506007
## nodefactor.deg.main.deg.pers.0.1         0.4615157492       0.48990203
## nodefactor.deg.main.deg.pers.0.2         0.2013104223       0.25042027
## nodefactor.deg.main.deg.pers.1.0         0.1928865884       0.23763000
## nodefactor.deg.main.deg.pers.1.1         0.3665109229       0.45201198
## nodefactor.deg.main.deg.pers.1.2         0.3845602784       0.45738353
## nodefactor.riskg.O3                      0.1037802653       0.10945269
## nodefactor.riskg.O4                      0.2889817923       0.38575122
## nodefactor.riskg.Y2                      0.0913656693       0.11164913
## nodefactor.riskg.Y3                      0.2877701963       0.33766103
## nodefactor.race..wa.B                    0.0007773791       0.35313669
## nodefactor.race..wa.H                   -0.0011505123       0.44596916
## nodefactor.region.EW                     0.2180313957       0.18849645
## nodefactor.region.OW                     0.4811897394       0.43755963
## nodematch.race..wa.B                     0.0014841620       0.08890996
## nodematch.race..wa.H                     0.0013760978       0.14758207
## nodematch.race..wa.O                     1.0000000000       0.69503619
## nodematch.region                         0.6950361909       1.00000000
## absdiff.sqrt.age                         0.5898710577       0.69051430
##                                  absdiff.sqrt.age
## edges                                  0.77321735
## nodefactor.deg.main.deg.pers.0.1       0.41842794
## nodefactor.deg.main.deg.pers.0.2       0.21046671
## nodefactor.deg.main.deg.pers.1.0       0.20676726
## nodefactor.deg.main.deg.pers.1.1       0.37786817
## nodefactor.deg.main.deg.pers.1.2       0.39946393
## nodefactor.riskg.O3                    0.11785102
## nodefactor.riskg.O4                    0.43421744
## nodefactor.riskg.Y2                    0.09276520
## nodefactor.riskg.Y3                    0.27513689
## nodefactor.race..wa.B                  0.30261040
## nodefactor.race..wa.H                  0.40395541
## nodefactor.region.EW                   0.25837813
## nodefactor.region.OW                   0.42084015
## nodematch.race..wa.B                   0.07478307
## nodematch.race..wa.H                   0.13240620
## nodematch.race..wa.O                   0.58987106
## nodematch.region                       0.69051430
## absdiff.sqrt.age                       1.00000000
## 
## Sample statistics auto-correlation:
## Chain 1 
##                edges nodefactor.deg.main.deg.pers.0.1
## Lag 0     1.00000000                       1.00000000
## Lag 1e+05 0.19173876                       0.29553230
## Lag 2e+05 0.09764222                       0.15894063
## Lag 3e+05 0.06965239                       0.10107121
## Lag 4e+05 0.06653555                       0.06192337
## Lag 5e+05 0.03663031                       0.05438959
##           nodefactor.deg.main.deg.pers.0.2
## Lag 0                          1.000000000
## Lag 1e+05                      0.048027179
## Lag 2e+05                      0.029519906
## Lag 3e+05                     -0.002333819
## Lag 4e+05                     -0.001614253
## Lag 5e+05                      0.025985235
##           nodefactor.deg.main.deg.pers.1.0
## Lag 0                          1.000000000
## Lag 1e+05                      0.001430527
## Lag 2e+05                     -0.019311044
## Lag 3e+05                      0.025876945
## Lag 4e+05                      0.014666028
## Lag 5e+05                     -0.014053158
##           nodefactor.deg.main.deg.pers.1.1
## Lag 0                           1.00000000
## Lag 1e+05                       0.30715457
## Lag 2e+05                       0.19926640
## Lag 3e+05                       0.11440171
## Lag 4e+05                       0.11061899
## Lag 5e+05                       0.09614892
##           nodefactor.deg.main.deg.pers.1.2 nodefactor.riskg.O3
## Lag 0                           1.00000000         1.000000000
## Lag 1e+05                       0.31614011         0.022712703
## Lag 2e+05                       0.18182030        -0.016561837
## Lag 3e+05                       0.10645294         0.006741233
## Lag 4e+05                       0.06324103        -0.019158527
## Lag 5e+05                       0.04876113         0.002287580
##           nodefactor.riskg.O4 nodefactor.riskg.Y2 nodefactor.riskg.Y3
## Lag 0              1.00000000         1.000000000         1.000000000
## Lag 1e+05          0.10527584         0.022250467         0.006422511
## Lag 2e+05          0.05293589         0.001192246         0.013894036
## Lag 3e+05          0.02228738        -0.004239066         0.011560671
## Lag 4e+05          0.03739752        -0.018518769        -0.016067485
## Lag 5e+05          0.01433896        -0.006469774         0.037473621
##           nodefactor.race..wa.B nodefactor.race..wa.H nodefactor.region.EW
## Lag 0                1.00000000            1.00000000            1.0000000
## Lag 1e+05            0.23434441            0.29262345            0.3630390
## Lag 2e+05            0.11880178            0.17297242            0.2508196
## Lag 3e+05            0.06886543            0.12479512            0.1737696
## Lag 4e+05            0.03624450            0.09512313            0.1734205
## Lag 5e+05            0.01784914            0.07887973            0.1337633
##           nodefactor.region.OW nodematch.race..wa.B nodematch.race..wa.H
## Lag 0               1.00000000           1.00000000            1.0000000
## Lag 1e+05           0.19382257           0.29243702            0.4325071
## Lag 2e+05           0.08304416           0.15016691            0.2880899
## Lag 3e+05           0.04397610           0.10343354            0.2059737
## Lag 4e+05           0.04560242           0.05151167            0.1570095
## Lag 5e+05           0.01051452           0.03580837            0.1289713
##           nodematch.race..wa.O nodematch.region absdiff.sqrt.age
## Lag 0               1.00000000       1.00000000       1.00000000
## Lag 1e+05           0.18556074       0.23978831       0.08707554
## Lag 2e+05           0.07595660       0.11197689       0.03491318
## Lag 3e+05           0.03184654       0.07489279       0.03124358
## Lag 4e+05           0.05393081       0.06523810       0.01797504
## Lag 5e+05           0.02431579       0.04055130      -0.01086627
## Chain 2 
##                edges nodefactor.deg.main.deg.pers.0.1
## Lag 0     1.00000000                       1.00000000
## Lag 1e+05 0.24013709                       0.31650944
## Lag 2e+05 0.08816983                       0.16272206
## Lag 3e+05 0.04050508                       0.06812468
## Lag 4e+05 0.02721286                       0.04244072
## Lag 5e+05 0.01722515                       0.02041771
##           nodefactor.deg.main.deg.pers.0.2
## Lag 0                          1.000000000
## Lag 1e+05                      0.056101382
## Lag 2e+05                     -0.013599520
## Lag 3e+05                      0.003042401
## Lag 4e+05                     -0.013861455
## Lag 5e+05                     -0.029120060
##           nodefactor.deg.main.deg.pers.1.0
## Lag 0                          1.000000000
## Lag 1e+05                      0.018174734
## Lag 2e+05                     -0.002420569
## Lag 3e+05                     -0.015810194
## Lag 4e+05                     -0.013973599
## Lag 5e+05                     -0.017832095
##           nodefactor.deg.main.deg.pers.1.1
## Lag 0                           1.00000000
## Lag 1e+05                       0.31211536
## Lag 2e+05                       0.19513698
## Lag 3e+05                       0.15124946
## Lag 4e+05                       0.08966042
## Lag 5e+05                       0.05949677
##           nodefactor.deg.main.deg.pers.1.2 nodefactor.riskg.O3
## Lag 0                           1.00000000        1.000000e+00
## Lag 1e+05                       0.35122310       -1.421399e-02
## Lag 2e+05                       0.21730889       -1.323882e-02
## Lag 3e+05                       0.13411928       -1.600652e-03
## Lag 4e+05                       0.07260502        9.647915e-03
## Lag 5e+05                       0.06376903       -9.405375e-05
##           nodefactor.riskg.O4 nodefactor.riskg.Y2 nodefactor.riskg.Y3
## Lag 0             1.000000000         1.000000000         1.000000000
## Lag 1e+05         0.146890880         0.002053739         0.012526356
## Lag 2e+05         0.036791850        -0.009561977         0.005943480
## Lag 3e+05         0.028211840        -0.011064424         0.005068848
## Lag 4e+05         0.006527617         0.006023085        -0.032046457
## Lag 5e+05         0.005941588         0.014665964        -0.009685792
##           nodefactor.race..wa.B nodefactor.race..wa.H nodefactor.region.EW
## Lag 0               1.000000000            1.00000000           1.00000000
## Lag 1e+05           0.232000300            0.34612357           0.36585928
## Lag 2e+05           0.104468377            0.18691563           0.24018772
## Lag 3e+05           0.047080494            0.13131361           0.16349267
## Lag 4e+05           0.042031934            0.09742653           0.14413398
## Lag 5e+05           0.009844213            0.06305013           0.08755481
##           nodefactor.region.OW nodematch.race..wa.B nodematch.race..wa.H
## Lag 0              1.000000000           1.00000000            1.0000000
## Lag 1e+05          0.188415123           0.33272778            0.4226504
## Lag 2e+05          0.089811508           0.17998147            0.2798680
## Lag 3e+05          0.045601281           0.11428957            0.2058351
## Lag 4e+05          0.033551969           0.07802161            0.1752585
## Lag 5e+05          0.004552246           0.07222909            0.1405604
##           nodematch.race..wa.O nodematch.region absdiff.sqrt.age
## Lag 0              1.000000000       1.00000000      1.000000000
## Lag 1e+05          0.201513106       0.27138778      0.137176313
## Lag 2e+05          0.076098572       0.11411620      0.044725916
## Lag 3e+05          0.042477568       0.05055771     -0.001533659
## Lag 4e+05          0.012301867       0.04043541      0.005694411
## Lag 5e+05         -0.007851541       0.03724182      0.011697148
## Chain 3 
##                 edges nodefactor.deg.main.deg.pers.0.1
## Lag 0     1.000000000                       1.00000000
## Lag 1e+05 0.167055911                       0.29774640
## Lag 2e+05 0.056885900                       0.14723873
## Lag 3e+05 0.034155529                       0.10514562
## Lag 4e+05 0.003935844                       0.08073595
## Lag 5e+05 0.014611843                       0.04627277
##           nodefactor.deg.main.deg.pers.0.2
## Lag 0                          1.000000000
## Lag 1e+05                      0.047492348
## Lag 2e+05                     -0.001341421
## Lag 3e+05                      0.024165764
## Lag 4e+05                      0.016310567
## Lag 5e+05                      0.008937241
##           nodefactor.deg.main.deg.pers.1.0
## Lag 0                          1.000000000
## Lag 1e+05                     -0.028083388
## Lag 2e+05                     -0.001325568
## Lag 3e+05                      0.016145545
## Lag 4e+05                      0.011657467
## Lag 5e+05                     -0.004575688
##           nodefactor.deg.main.deg.pers.1.1
## Lag 0                           1.00000000
## Lag 1e+05                       0.30550365
## Lag 2e+05                       0.17403424
## Lag 3e+05                       0.11159183
## Lag 4e+05                       0.07302904
## Lag 5e+05                       0.02456749
##           nodefactor.deg.main.deg.pers.1.2 nodefactor.riskg.O3
## Lag 0                           1.00000000        1.0000000000
## Lag 1e+05                       0.29175843        0.0237908708
## Lag 2e+05                       0.14041682        0.0146710283
## Lag 3e+05                       0.06992443       -0.0009648373
## Lag 4e+05                       0.02250793       -0.0181915086
## Lag 5e+05                       0.02491789       -0.0022804600
##           nodefactor.riskg.O4 nodefactor.riskg.Y2 nodefactor.riskg.Y3
## Lag 0              1.00000000         1.000000000          1.00000000
## Lag 1e+05          0.11087539         0.004368934         -0.01594903
## Lag 2e+05          0.03996922         0.003045722         -0.01511376
## Lag 3e+05          0.03472664        -0.016374422          0.03923252
## Lag 4e+05          0.02311444         0.008001105         -0.02257919
## Lag 5e+05          0.01150124         0.003904963         -0.01482413
##           nodefactor.race..wa.B nodefactor.race..wa.H nodefactor.region.EW
## Lag 0                1.00000000            1.00000000            1.0000000
## Lag 1e+05            0.26323745            0.28357771            0.3388131
## Lag 2e+05            0.12810485            0.17294764            0.2218310
## Lag 3e+05            0.07218972            0.12279377            0.1652505
## Lag 4e+05            0.05362696            0.04717534            0.1342910
## Lag 5e+05            0.02677583            0.03968706            0.0980300
##           nodefactor.region.OW nodematch.race..wa.B nodematch.race..wa.H
## Lag 0               1.00000000           1.00000000            1.0000000
## Lag 1e+05           0.18311551           0.31760104            0.3835897
## Lag 2e+05           0.08983810           0.17286552            0.2582052
## Lag 3e+05           0.07715199           0.13275315            0.1788250
## Lag 4e+05           0.01696687           0.10801237            0.1341556
## Lag 5e+05           0.01772260           0.06222814            0.1020846
##           nodematch.race..wa.O nodematch.region absdiff.sqrt.age
## Lag 0               1.00000000       1.00000000     1.000000e+00
## Lag 1e+05           0.14711613       0.20481585     1.077353e-01
## Lag 2e+05           0.06691739       0.07174836     3.670464e-02
## Lag 3e+05           0.02626206       0.04974480     3.872789e-03
## Lag 4e+05           0.02847253       0.02288884     1.835038e-05
## Lag 5e+05           0.03107474       0.02150171     1.079323e-02
## Chain 4 
##                edges nodefactor.deg.main.deg.pers.0.1
## Lag 0     1.00000000                       1.00000000
## Lag 1e+05 0.23848983                       0.34026600
## Lag 2e+05 0.10432844                       0.19620088
## Lag 3e+05 0.07103457                       0.12913131
## Lag 4e+05 0.02129242                       0.07949622
## Lag 5e+05 0.03170337                       0.03660791
##           nodefactor.deg.main.deg.pers.0.2
## Lag 0                          1.000000000
## Lag 1e+05                      0.070670919
## Lag 2e+05                      0.011280757
## Lag 3e+05                     -0.005374838
## Lag 4e+05                     -0.009358528
## Lag 5e+05                      0.014219573
##           nodefactor.deg.main.deg.pers.1.0
## Lag 0                           1.00000000
## Lag 1e+05                      -0.03253820
## Lag 2e+05                       0.02671449
## Lag 3e+05                      -0.01494958
## Lag 4e+05                      -0.01894379
## Lag 5e+05                      -0.01393642
##           nodefactor.deg.main.deg.pers.1.1
## Lag 0                           1.00000000
## Lag 1e+05                       0.29896324
## Lag 2e+05                       0.14774922
## Lag 3e+05                       0.07874275
## Lag 4e+05                       0.06462772
## Lag 5e+05                       0.05521713
##           nodefactor.deg.main.deg.pers.1.2 nodefactor.riskg.O3
## Lag 0                           1.00000000        1.0000000000
## Lag 1e+05                       0.35165901        0.0192437684
## Lag 2e+05                       0.18898394        0.0189553348
## Lag 3e+05                       0.12697289        0.0061400039
## Lag 4e+05                       0.09810259        0.0299459071
## Lag 5e+05                       0.04438754        0.0003961651
##           nodefactor.riskg.O4 nodefactor.riskg.Y2 nodefactor.riskg.Y3
## Lag 0              1.00000000         1.000000000         1.000000000
## Lag 1e+05          0.13862250         0.021525643         0.008165880
## Lag 2e+05          0.04664381         0.007766675         0.034060225
## Lag 3e+05          0.01006810        -0.014598958         0.014571928
## Lag 4e+05          0.02134356        -0.024742072        -0.008357306
## Lag 5e+05          0.04132923         0.008331415        -0.017736989
##           nodefactor.race..wa.B nodefactor.race..wa.H nodefactor.region.EW
## Lag 0                1.00000000            1.00000000           1.00000000
## Lag 1e+05            0.26060033            0.32719884           0.31787746
## Lag 2e+05            0.14852526            0.20504506           0.21987186
## Lag 3e+05            0.09448202            0.13616167           0.14821845
## Lag 4e+05            0.02846825            0.09435218           0.11870121
## Lag 5e+05            0.02882033            0.09977177           0.09919947
##           nodefactor.region.OW nodematch.race..wa.B nodematch.race..wa.H
## Lag 0               1.00000000           1.00000000            1.0000000
## Lag 1e+05           0.21089720           0.29027284            0.4057907
## Lag 2e+05           0.08801838           0.17367541            0.2853188
## Lag 3e+05           0.06865370           0.11162544            0.2174550
## Lag 4e+05           0.03774244           0.05572229            0.1777266
## Lag 5e+05           0.01935947           0.03446826            0.1447663
##           nodematch.race..wa.O nodematch.region absdiff.sqrt.age
## Lag 0              1.000000000       1.00000000       1.00000000
## Lag 1e+05          0.176405527       0.27851422       0.14049912
## Lag 2e+05          0.053234807       0.11969452       0.01644901
## Lag 3e+05          0.064848138       0.07097314       0.01910794
## Lag 4e+05          0.013324480       0.03985962       0.00116933
## Lag 5e+05         -0.008447623       0.03746660       0.01623205
## Chain 5 
##                edges nodefactor.deg.main.deg.pers.0.1
## Lag 0     1.00000000                       1.00000000
## Lag 1e+05 0.20566948                       0.31495444
## Lag 2e+05 0.10384990                       0.15569789
## Lag 3e+05 0.05015300                       0.10174471
## Lag 4e+05 0.05712862                       0.07286382
## Lag 5e+05 0.01693187                       0.05919131
##           nodefactor.deg.main.deg.pers.0.2
## Lag 0                          1.000000000
## Lag 1e+05                      0.038616175
## Lag 2e+05                      0.002989034
## Lag 3e+05                     -0.013073347
## Lag 4e+05                     -0.016264102
## Lag 5e+05                     -0.008131310
##           nodefactor.deg.main.deg.pers.1.0
## Lag 0                          1.000000000
## Lag 1e+05                      0.008789335
## Lag 2e+05                     -0.009403613
## Lag 3e+05                      0.019982321
## Lag 4e+05                      0.034030158
## Lag 5e+05                      0.012830858
##           nodefactor.deg.main.deg.pers.1.1
## Lag 0                           1.00000000
## Lag 1e+05                       0.32045740
## Lag 2e+05                       0.16736502
## Lag 3e+05                       0.12023350
## Lag 4e+05                       0.08756943
## Lag 5e+05                       0.05567568
##           nodefactor.deg.main.deg.pers.1.2 nodefactor.riskg.O3
## Lag 0                           1.00000000         1.000000000
## Lag 1e+05                       0.30290494         0.021999068
## Lag 2e+05                       0.18715978         0.021222256
## Lag 3e+05                       0.09815597         0.010657824
## Lag 4e+05                       0.06510247         0.006242909
## Lag 5e+05                       0.03426485         0.027110192
##           nodefactor.riskg.O4 nodefactor.riskg.Y2 nodefactor.riskg.Y3
## Lag 0             1.000000000         1.000000000         1.000000000
## Lag 1e+05         0.112536859        -0.002712048        -0.015431231
## Lag 2e+05         0.058381075        -0.010989468        -0.012217833
## Lag 3e+05         0.035446238        -0.006746428        -0.002602155
## Lag 4e+05         0.029505485        -0.017606747        -0.022881525
## Lag 5e+05         0.005727452        -0.014929236         0.021390992
##           nodefactor.race..wa.B nodefactor.race..wa.H nodefactor.region.EW
## Lag 0                1.00000000            1.00000000           1.00000000
## Lag 1e+05            0.23624068            0.28411393           0.32118134
## Lag 2e+05            0.15285272            0.17421653           0.19717535
## Lag 3e+05            0.07996567            0.09766509           0.14664319
## Lag 4e+05            0.07464796            0.05122368           0.12005002
## Lag 5e+05            0.03922609            0.03565607           0.07876835
##           nodefactor.region.OW nodematch.race..wa.B nodematch.race..wa.H
## Lag 0               1.00000000           1.00000000            1.0000000
## Lag 1e+05           0.21901304           0.30205205            0.3638392
## Lag 2e+05           0.12783429           0.20026428            0.2674607
## Lag 3e+05           0.05878452           0.09754058            0.1938920
## Lag 4e+05           0.02692702           0.05560476            0.1409356
## Lag 5e+05           0.02739730           0.05419514            0.1171262
##           nodematch.race..wa.O nodematch.region absdiff.sqrt.age
## Lag 0               1.00000000       1.00000000      1.000000000
## Lag 1e+05           0.17194060       0.23427055      0.101044403
## Lag 2e+05           0.07970956       0.11410739      0.045290679
## Lag 3e+05           0.04317282       0.06910353     -0.004530258
## Lag 4e+05           0.06081571       0.05359422      0.023934441
## Lag 5e+05           0.02664680       0.03270409     -0.007646500
## Chain 6 
##                edges nodefactor.deg.main.deg.pers.0.1
## Lag 0     1.00000000                       1.00000000
## Lag 1e+05 0.21807264                       0.30517085
## Lag 2e+05 0.06809007                       0.16075375
## Lag 3e+05 0.03386069                       0.07500314
## Lag 4e+05 0.01211059                       0.06190667
## Lag 5e+05 0.02340494                       0.04712570
##           nodefactor.deg.main.deg.pers.0.2
## Lag 0                          1.000000000
## Lag 1e+05                      0.011598562
## Lag 2e+05                     -0.018009349
## Lag 3e+05                      0.002199201
## Lag 4e+05                      0.017585285
## Lag 5e+05                     -0.023614227
##           nodefactor.deg.main.deg.pers.1.0
## Lag 0                          1.000000000
## Lag 1e+05                     -0.014574761
## Lag 2e+05                      0.001018407
## Lag 3e+05                     -0.021683112
## Lag 4e+05                      0.019938234
## Lag 5e+05                     -0.015559804
##           nodefactor.deg.main.deg.pers.1.1
## Lag 0                           1.00000000
## Lag 1e+05                       0.32626780
## Lag 2e+05                       0.17600669
## Lag 3e+05                       0.11644544
## Lag 4e+05                       0.08834934
## Lag 5e+05                       0.07125512
##           nodefactor.deg.main.deg.pers.1.2 nodefactor.riskg.O3
## Lag 0                           1.00000000          1.00000000
## Lag 1e+05                       0.27660489         -0.01913345
## Lag 2e+05                       0.14434605         -0.01214181
## Lag 3e+05                       0.09066479         -0.01768335
## Lag 4e+05                       0.05012347          0.01875767
## Lag 5e+05                       0.06402386          0.03134832
##           nodefactor.riskg.O4 nodefactor.riskg.Y2 nodefactor.riskg.Y3
## Lag 0              1.00000000         1.000000000          1.00000000
## Lag 1e+05          0.10897351         0.029863138          0.01421481
## Lag 2e+05          0.04622988        -0.008035964         -0.01472431
## Lag 3e+05          0.01666076         0.015392671         -0.01776789
## Lag 4e+05         -0.02220093         0.024678677          0.03085070
## Lag 5e+05         -0.01020881        -0.026993435          0.03078933
##           nodefactor.race..wa.B nodefactor.race..wa.H nodefactor.region.EW
## Lag 0                1.00000000            1.00000000            1.0000000
## Lag 1e+05            0.21768348            0.32314905            0.3244362
## Lag 2e+05            0.13502397            0.19739069            0.2322363
## Lag 3e+05            0.06213949            0.12782750            0.1764162
## Lag 4e+05            0.02917587            0.09223941            0.1367592
## Lag 5e+05            0.01150740            0.08312174            0.1156429
##           nodefactor.region.OW nodematch.race..wa.B nodematch.race..wa.H
## Lag 0               1.00000000           1.00000000            1.0000000
## Lag 1e+05           0.19261417           0.28991438            0.4279893
## Lag 2e+05           0.05340299           0.16781819            0.2791071
## Lag 3e+05           0.03316085           0.10499468            0.2140794
## Lag 4e+05          -0.01003622           0.07518493            0.1570234
## Lag 5e+05          -0.01680307           0.04377855            0.1354038
##           nodematch.race..wa.O nodematch.region absdiff.sqrt.age
## Lag 0              1.000000000       1.00000000      1.000000000
## Lag 1e+05          0.185229827       0.26474794      0.129601106
## Lag 2e+05          0.047630927       0.09883226      0.027676024
## Lag 3e+05          0.018972692       0.07094443     -0.002170784
## Lag 4e+05          0.015069740       0.02512910     -0.026402548
## Lag 5e+05          0.009118408       0.01716262      0.002672108
## Chain 7 
##                edges nodefactor.deg.main.deg.pers.0.1
## Lag 0     1.00000000                       1.00000000
## Lag 1e+05 0.21053295                       0.28935379
## Lag 2e+05 0.12985034                       0.18607002
## Lag 3e+05 0.07635701                       0.10507361
## Lag 4e+05 0.03843508                       0.06048246
## Lag 5e+05 0.05317309                       0.02222478
##           nodefactor.deg.main.deg.pers.0.2
## Lag 0                         1.0000000000
## Lag 1e+05                     0.0529139444
## Lag 2e+05                     0.0006248598
## Lag 3e+05                     0.0080384739
## Lag 4e+05                     0.0193115500
## Lag 5e+05                    -0.0051945322
##           nodefactor.deg.main.deg.pers.1.0
## Lag 0                          1.000000000
## Lag 1e+05                      0.023379080
## Lag 2e+05                     -0.018049281
## Lag 3e+05                      0.003760484
## Lag 4e+05                     -0.002701123
## Lag 5e+05                     -0.016996729
##           nodefactor.deg.main.deg.pers.1.1
## Lag 0                           1.00000000
## Lag 1e+05                       0.34078649
## Lag 2e+05                       0.20032800
## Lag 3e+05                       0.12353586
## Lag 4e+05                       0.08492469
## Lag 5e+05                       0.06979101
##           nodefactor.deg.main.deg.pers.1.2 nodefactor.riskg.O3
## Lag 0                           1.00000000         1.000000000
## Lag 1e+05                       0.29544234        -0.002285879
## Lag 2e+05                       0.12798732        -0.021796407
## Lag 3e+05                       0.06559046        -0.021672691
## Lag 4e+05                       0.04192819         0.011902197
## Lag 5e+05                       0.04720056         0.002780622
##           nodefactor.riskg.O4 nodefactor.riskg.Y2 nodefactor.riskg.Y3
## Lag 0              1.00000000         1.000000000         1.000000000
## Lag 1e+05          0.11712551        -0.014906572         0.001602972
## Lag 2e+05          0.04312621         0.004579393        -0.002696719
## Lag 3e+05          0.05755532         0.022158087        -0.034367395
## Lag 4e+05          0.01884851        -0.007412513        -0.018653662
## Lag 5e+05          0.01549958         0.006639043         0.025736874
##           nodefactor.race..wa.B nodefactor.race..wa.H nodefactor.region.EW
## Lag 0                1.00000000            1.00000000           1.00000000
## Lag 1e+05            0.25877839            0.31755880           0.30318575
## Lag 2e+05            0.14509087            0.20732609           0.21680903
## Lag 3e+05            0.10260308            0.13406946           0.11589284
## Lag 4e+05            0.08031877            0.08153897           0.09006354
## Lag 5e+05            0.07004292            0.06144469           0.06507271
##           nodefactor.region.OW nodematch.race..wa.B nodematch.race..wa.H
## Lag 0               1.00000000           1.00000000            1.0000000
## Lag 1e+05           0.20286901           0.28783616            0.3894614
## Lag 2e+05           0.12938339           0.16184802            0.2638032
## Lag 3e+05           0.06330016           0.11467185            0.1951961
## Lag 4e+05           0.03561001           0.04655690            0.1534829
## Lag 5e+05           0.02778209           0.04310919            0.1427636
##           nodematch.race..wa.O nodematch.region absdiff.sqrt.age
## Lag 0               1.00000000       1.00000000       1.00000000
## Lag 1e+05           0.18777686       0.25472892       0.11041157
## Lag 2e+05           0.10379200       0.12109043       0.02228423
## Lag 3e+05           0.05361570       0.08461371       0.02450302
## Lag 4e+05           0.03786288       0.05757735       0.01116055
## Lag 5e+05           0.04453575       0.06196534       0.02518580
## Chain 8 
##                 edges nodefactor.deg.main.deg.pers.0.1
## Lag 0     1.000000000                       1.00000000
## Lag 1e+05 0.185581036                       0.31739797
## Lag 2e+05 0.077977550                       0.16719776
## Lag 3e+05 0.024748145                       0.06540102
## Lag 4e+05 0.032296108                       0.07419181
## Lag 5e+05 0.002647112                       0.03218604
##           nodefactor.deg.main.deg.pers.0.2
## Lag 0                           1.00000000
## Lag 1e+05                       0.06923821
## Lag 2e+05                      -0.01183036
## Lag 3e+05                      -0.01812645
## Lag 4e+05                      -0.01116312
## Lag 5e+05                       0.02086398
##           nodefactor.deg.main.deg.pers.1.0
## Lag 0                          1.000000000
## Lag 1e+05                      0.018900330
## Lag 2e+05                      0.006295372
## Lag 3e+05                     -0.007824448
## Lag 4e+05                      0.020727229
## Lag 5e+05                      0.012396751
##           nodefactor.deg.main.deg.pers.1.1
## Lag 0                           1.00000000
## Lag 1e+05                       0.28419218
## Lag 2e+05                       0.15319129
## Lag 3e+05                       0.08485995
## Lag 4e+05                       0.05391667
## Lag 5e+05                       0.02269593
##           nodefactor.deg.main.deg.pers.1.2 nodefactor.riskg.O3
## Lag 0                           1.00000000         1.000000000
## Lag 1e+05                       0.29643358        -0.014649222
## Lag 2e+05                       0.16875898         0.026767136
## Lag 3e+05                       0.10402296         0.001718842
## Lag 4e+05                       0.08434689        -0.007587217
## Lag 5e+05                       0.04243569         0.002874885
##           nodefactor.riskg.O4 nodefactor.riskg.Y2 nodefactor.riskg.Y3
## Lag 0            1.0000000000        1.0000000000         1.000000000
## Lag 1e+05        0.1320293722       -0.0226061187         0.021472663
## Lag 2e+05        0.0729152787       -0.0210728063         0.007104583
## Lag 3e+05        0.0368940939        0.0162694346        -0.030386316
## Lag 4e+05        0.0009066786       -0.0003090838        -0.021831120
## Lag 5e+05        0.0210151312       -0.0013604531        -0.006398078
##           nodefactor.race..wa.B nodefactor.race..wa.H nodefactor.region.EW
## Lag 0               1.000000000            1.00000000           1.00000000
## Lag 1e+05           0.242241160            0.29525000           0.33306958
## Lag 2e+05           0.111036978            0.14825275           0.22021154
## Lag 3e+05           0.072120419            0.09142207           0.16503311
## Lag 4e+05           0.017913761            0.06784109           0.13541977
## Lag 5e+05           0.006255107            0.05099074           0.09481549
##           nodefactor.region.OW nodematch.race..wa.B nodematch.race..wa.H
## Lag 0              1.000000000           1.00000000            1.0000000
## Lag 1e+05          0.170408107           0.31369051            0.3996904
## Lag 2e+05          0.060461160           0.17447864            0.2762852
## Lag 3e+05          0.016891531           0.09871003            0.2257577
## Lag 4e+05          0.020589901           0.05728132            0.1777642
## Lag 5e+05          0.003875981           0.03718662            0.1421868
##           nodematch.race..wa.O nodematch.region absdiff.sqrt.age
## Lag 0               1.00000000      1.000000000       1.00000000
## Lag 1e+05           0.14932723      0.233029354       0.08452641
## Lag 2e+05           0.08279835      0.098872764       0.02698716
## Lag 3e+05           0.01461446      0.043403464       0.00185019
## Lag 4e+05           0.04393848      0.034497162       0.01716604
## Lag 5e+05           0.01339102     -0.001569331      -0.02631844
## 
## Sample statistics burn-in diagnostic (Geweke):
## Chain 8 
## 
## Fraction in 1st window = 0.1
## Fraction in 2nd window = 0.5 
## 
##                            edges nodefactor.deg.main.deg.pers.0.1 
##                           2.2852                           1.3079 
## nodefactor.deg.main.deg.pers.0.2 nodefactor.deg.main.deg.pers.1.0 
##                          -1.4247                          -0.6634 
## nodefactor.deg.main.deg.pers.1.1 nodefactor.deg.main.deg.pers.1.2 
##                           1.5022                           1.7586 
##              nodefactor.riskg.O3              nodefactor.riskg.O4 
##                           0.3149                           1.7219 
##              nodefactor.riskg.Y2              nodefactor.riskg.Y3 
##                           1.6488                          -0.4800 
##            nodefactor.race..wa.B            nodefactor.race..wa.H 
##                           0.7071                           0.8093 
##             nodefactor.region.EW             nodefactor.region.OW 
##                           1.8461                           1.8715 
##             nodematch.race..wa.B             nodematch.race..wa.H 
##                           0.4076                           1.6387 
##             nodematch.race..wa.O                 nodematch.region 
##                           2.4444                           2.5754 
##                 absdiff.sqrt.age 
##                           1.9043 
## 
## Individual P-values (lower = worse):
##                            edges nodefactor.deg.main.deg.pers.0.1 
##                       0.02230331                       0.19092026 
## nodefactor.deg.main.deg.pers.0.2 nodefactor.deg.main.deg.pers.1.0 
##                       0.15424344                       0.50710312 
## nodefactor.deg.main.deg.pers.1.1 nodefactor.deg.main.deg.pers.1.2 
##                       0.13303865                       0.07865254 
##              nodefactor.riskg.O3              nodefactor.riskg.O4 
##                       0.75283838                       0.08508909 
##              nodefactor.riskg.Y2              nodefactor.riskg.Y3 
##                       0.09919469                       0.63119252 
##            nodefactor.race..wa.B            nodefactor.race..wa.H 
##                       0.47951007                       0.41831866 
##             nodefactor.region.EW             nodefactor.region.OW 
##                       0.06488265                       0.06127621 
##             nodematch.race..wa.B             nodematch.race..wa.H 
##                       0.68360114                       0.10127644 
##             nodematch.race..wa.O                 nodematch.region 
##                       0.01451130                       0.01001342 
##                 absdiff.sqrt.age 
##                       0.05687414 
## Joint P-value (lower = worse):  1 .
## Chain 8 
## 
## Fraction in 1st window = 0.1
## Fraction in 2nd window = 0.5 
## 
##                            edges nodefactor.deg.main.deg.pers.0.1 
##                          -1.4434                          -0.2992 
## nodefactor.deg.main.deg.pers.0.2 nodefactor.deg.main.deg.pers.1.0 
##                           0.4001                          -1.6096 
## nodefactor.deg.main.deg.pers.1.1 nodefactor.deg.main.deg.pers.1.2 
##                          -0.1149                          -0.8093 
##              nodefactor.riskg.O3              nodefactor.riskg.O4 
##                          -1.4537                          -1.0079 
##              nodefactor.riskg.Y2              nodefactor.riskg.Y3 
##                          -0.3018                           0.1093 
##            nodefactor.race..wa.B            nodefactor.race..wa.H 
##                           0.7947                          -1.9996 
##             nodefactor.region.EW             nodefactor.region.OW 
##                          -0.7052                          -0.5196 
##             nodematch.race..wa.B             nodematch.race..wa.H 
##                           0.6128                          -0.9763 
##             nodematch.race..wa.O                 nodematch.region 
##                          -0.9044                          -1.4090 
##                 absdiff.sqrt.age 
##                          -1.1199 
## 
## Individual P-values (lower = worse):
##                            edges nodefactor.deg.main.deg.pers.0.1 
##                       0.14889633                       0.76476875 
## nodefactor.deg.main.deg.pers.0.2 nodefactor.deg.main.deg.pers.1.0 
##                       0.68906554                       0.10749467 
## nodefactor.deg.main.deg.pers.1.1 nodefactor.deg.main.deg.pers.1.2 
##                       0.90850888                       0.41835324 
##              nodefactor.riskg.O3              nodefactor.riskg.O4 
##                       0.14604048                       0.31348387 
##              nodefactor.riskg.Y2              nodefactor.riskg.Y3 
##                       0.76282719                       0.91295328 
##            nodefactor.race..wa.B            nodefactor.race..wa.H 
##                       0.42678026                       0.04554003 
##             nodefactor.region.EW             nodefactor.region.OW 
##                       0.48066381                       0.60337717 
##             nodematch.race..wa.B             nodematch.race..wa.H 
##                       0.53999998                       0.32893932 
##             nodematch.race..wa.O                 nodematch.region 
##                       0.36577954                       0.15884113 
##                 absdiff.sqrt.age 
##                       0.26275945 
## Joint P-value (lower = worse):  0.9767558 .
## Chain 8 
## 
## Fraction in 1st window = 0.1
## Fraction in 2nd window = 0.5 
## 
##                            edges nodefactor.deg.main.deg.pers.0.1 
##                          1.78639                          0.46751 
## nodefactor.deg.main.deg.pers.0.2 nodefactor.deg.main.deg.pers.1.0 
##                         -0.53966                         -0.05748 
## nodefactor.deg.main.deg.pers.1.1 nodefactor.deg.main.deg.pers.1.2 
##                          0.71256                          1.10260 
##              nodefactor.riskg.O3              nodefactor.riskg.O4 
##                         -0.00734                          0.58430 
##              nodefactor.riskg.Y2              nodefactor.riskg.Y3 
##                         -0.62953                         -0.91125 
##            nodefactor.race..wa.B            nodefactor.race..wa.H 
##                          0.99426                          0.19439 
##             nodefactor.region.EW             nodefactor.region.OW 
##                         -1.03499                          1.25258 
##             nodematch.race..wa.B             nodematch.race..wa.H 
##                          1.70684                         -1.42237 
##             nodematch.race..wa.O                 nodematch.region 
##                          1.26924                          1.39130 
##                 absdiff.sqrt.age 
##                          1.25631 
## 
## Individual P-values (lower = worse):
##                            edges nodefactor.deg.main.deg.pers.0.1 
##                       0.07403614                       0.64013646 
## nodefactor.deg.main.deg.pers.0.2 nodefactor.deg.main.deg.pers.1.0 
##                       0.58943338                       0.95416455 
## nodefactor.deg.main.deg.pers.1.1 nodefactor.deg.main.deg.pers.1.2 
##                       0.47611650                       0.27020156 
##              nodefactor.riskg.O3              nodefactor.riskg.O4 
##                       0.99414341                       0.55902132 
##              nodefactor.riskg.Y2              nodefactor.riskg.Y3 
##                       0.52900074                       0.36216200 
##            nodefactor.race..wa.B            nodefactor.race..wa.H 
##                       0.32009644                       0.84587028 
##             nodefactor.region.EW             nodefactor.region.OW 
##                       0.30067371                       0.21036009 
##             nodematch.race..wa.B             nodematch.race..wa.H 
##                       0.08785088                       0.15491860 
##             nodematch.race..wa.O                 nodematch.region 
##                       0.20435479                       0.16413472 
##                 absdiff.sqrt.age 
##                       0.20900338 
## Joint P-value (lower = worse):  1 .
## Chain 8 
## 
## Fraction in 1st window = 0.1
## Fraction in 2nd window = 0.5 
## 
##                            edges nodefactor.deg.main.deg.pers.0.1 
##                        -0.835350                        -0.404192 
## nodefactor.deg.main.deg.pers.0.2 nodefactor.deg.main.deg.pers.1.0 
##                        -0.617472                        -1.254774 
## nodefactor.deg.main.deg.pers.1.1 nodefactor.deg.main.deg.pers.1.2 
##                        -1.856703                         0.881783 
##              nodefactor.riskg.O3              nodefactor.riskg.O4 
##                        -1.108273                        -0.002741 
##              nodefactor.riskg.Y2              nodefactor.riskg.Y3 
##                         1.672968                         0.357563 
##            nodefactor.race..wa.B            nodefactor.race..wa.H 
##                         1.019745                        -2.196457 
##             nodefactor.region.EW             nodefactor.region.OW 
##                        -2.941851                        -1.013437 
##             nodematch.race..wa.B             nodematch.race..wa.H 
##                         0.888698                        -1.004352 
##             nodematch.race..wa.O                 nodematch.region 
##                        -0.205062                        -0.619324 
##                 absdiff.sqrt.age 
##                         0.425785 
## 
## Individual P-values (lower = worse):
##                            edges nodefactor.deg.main.deg.pers.0.1 
##                      0.403520950                      0.686071351 
## nodefactor.deg.main.deg.pers.0.2 nodefactor.deg.main.deg.pers.1.0 
##                      0.536923758                      0.209560759 
## nodefactor.deg.main.deg.pers.1.1 nodefactor.deg.main.deg.pers.1.2 
##                      0.063353415                      0.377894088 
##              nodefactor.riskg.O3              nodefactor.riskg.O4 
##                      0.267744093                      0.997812960 
##              nodefactor.riskg.Y2              nodefactor.riskg.Y3 
##                      0.094333572                      0.720670415 
##            nodefactor.race..wa.B            nodefactor.race..wa.H 
##                      0.307849375                      0.028059283 
##             nodefactor.region.EW             nodefactor.region.OW 
##                      0.003262573                      0.310851258 
##             nodematch.race..wa.B             nodematch.race..wa.H 
##                      0.374165608                      0.315208960 
##             nodematch.race..wa.O                 nodematch.region 
##                      0.837523926                      0.535703224 
##                 absdiff.sqrt.age 
##                      0.670264879 
## Joint P-value (lower = worse):  0.01113013 .
## Chain 8 
## 
## Fraction in 1st window = 0.1
## Fraction in 2nd window = 0.5 
## 
##                            edges nodefactor.deg.main.deg.pers.0.1 
##                         1.475496                        -0.115297 
## nodefactor.deg.main.deg.pers.0.2 nodefactor.deg.main.deg.pers.1.0 
##                        -0.145503                        -0.063612 
## nodefactor.deg.main.deg.pers.1.1 nodefactor.deg.main.deg.pers.1.2 
##                         0.597234                         1.523769 
##              nodefactor.riskg.O3              nodefactor.riskg.O4 
##                         0.006298                         0.607736 
##              nodefactor.riskg.Y2              nodefactor.riskg.Y3 
##                        -1.161335                        -0.142838 
##            nodefactor.race..wa.B            nodefactor.race..wa.H 
##                         0.107070                         1.588233 
##             nodefactor.region.EW             nodefactor.region.OW 
##                        -0.564120                        -0.121063 
##             nodematch.race..wa.B             nodematch.race..wa.H 
##                         0.678465                         0.434220 
##             nodematch.race..wa.O                 nodematch.region 
##                         0.396667                         1.719448 
##                 absdiff.sqrt.age 
##                         0.794187 
## 
## Individual P-values (lower = worse):
##                            edges nodefactor.deg.main.deg.pers.0.1 
##                       0.14007935                       0.90820951 
## nodefactor.deg.main.deg.pers.0.2 nodefactor.deg.main.deg.pers.1.0 
##                       0.88431368                       0.94927910 
## nodefactor.deg.main.deg.pers.1.1 nodefactor.deg.main.deg.pers.1.2 
##                       0.55035139                       0.12756638 
##              nodefactor.riskg.O3              nodefactor.riskg.O4 
##                       0.99497462                       0.54336230 
##              nodefactor.riskg.Y2              nodefactor.riskg.Y3 
##                       0.24550555                       0.88641852 
##            nodefactor.race..wa.B            nodefactor.race..wa.H 
##                       0.91473328                       0.11223360 
##             nodefactor.region.EW             nodefactor.region.OW 
##                       0.57267232                       0.90364133 
##             nodematch.race..wa.B             nodematch.race..wa.H 
##                       0.49747693                       0.66412857 
##             nodematch.race..wa.O                 nodematch.region 
##                       0.69161334                       0.08553286 
##                 absdiff.sqrt.age 
##                       0.42708672 
## Joint P-value (lower = worse):  0.02803736 .
## Chain 8 
## 
## Fraction in 1st window = 0.1
## Fraction in 2nd window = 0.5 
## 
##                            edges nodefactor.deg.main.deg.pers.0.1 
##                           1.5843                          -1.0149 
## nodefactor.deg.main.deg.pers.0.2 nodefactor.deg.main.deg.pers.1.0 
##                          -0.1124                           1.3303 
## nodefactor.deg.main.deg.pers.1.1 nodefactor.deg.main.deg.pers.1.2 
##                           1.9868                           1.5478 
##              nodefactor.riskg.O3              nodefactor.riskg.O4 
##                          -0.1654                          -1.4458 
##              nodefactor.riskg.Y2              nodefactor.riskg.Y3 
##                           0.4109                           1.1207 
##            nodefactor.race..wa.B            nodefactor.race..wa.H 
##                          -0.5444                           0.8648 
##             nodefactor.region.EW             nodefactor.region.OW 
##                           0.4938                           2.2323 
##             nodematch.race..wa.B             nodematch.race..wa.H 
##                           1.1209                           0.0293 
##             nodematch.race..wa.O                 nodematch.region 
##                           1.4192                           1.3324 
##                 absdiff.sqrt.age 
##                           0.6475 
## 
## Individual P-values (lower = worse):
##                            edges nodefactor.deg.main.deg.pers.0.1 
##                       0.11312607                       0.31015609 
## nodefactor.deg.main.deg.pers.0.2 nodefactor.deg.main.deg.pers.1.0 
##                       0.91048151                       0.18341670 
## nodefactor.deg.main.deg.pers.1.1 nodefactor.deg.main.deg.pers.1.2 
##                       0.04694308                       0.12167911 
##              nodefactor.riskg.O3              nodefactor.riskg.O4 
##                       0.86866001                       0.14822195 
##              nodefactor.riskg.Y2              nodefactor.riskg.Y3 
##                       0.68115602                       0.26239589 
##            nodefactor.race..wa.B            nodefactor.race..wa.H 
##                       0.58616840                       0.38717228 
##             nodefactor.region.EW             nodefactor.region.OW 
##                       0.62142484                       0.02559395 
##             nodematch.race..wa.B             nodematch.race..wa.H 
##                       0.26233690                       0.97662704 
##             nodematch.race..wa.O                 nodematch.region 
##                       0.15582694                       0.18272423 
##                 absdiff.sqrt.age 
##                       0.51728849 
## Joint P-value (lower = worse):  0.1255361 .
## Chain 8 
## 
## Fraction in 1st window = 0.1
## Fraction in 2nd window = 0.5 
## 
##                            edges nodefactor.deg.main.deg.pers.0.1 
##                         -0.72447                          0.69250 
## nodefactor.deg.main.deg.pers.0.2 nodefactor.deg.main.deg.pers.1.0 
##                          1.03444                         -0.16282 
## nodefactor.deg.main.deg.pers.1.1 nodefactor.deg.main.deg.pers.1.2 
##                         -1.35677                         -0.81141 
##              nodefactor.riskg.O3              nodefactor.riskg.O4 
##                         -0.32688                          0.49076 
##              nodefactor.riskg.Y2              nodefactor.riskg.Y3 
##                         -0.89151                         -0.98783 
##            nodefactor.race..wa.B            nodefactor.race..wa.H 
##                          1.63580                         -1.26856 
##             nodefactor.region.EW             nodefactor.region.OW 
##                         -0.52721                         -0.41718 
##             nodematch.race..wa.B             nodematch.race..wa.H 
##                          1.78173                         -2.03753 
##             nodematch.race..wa.O                 nodematch.region 
##                         -1.03666                          0.03752 
##                 absdiff.sqrt.age 
##                         -2.05450 
## 
## Individual P-values (lower = worse):
##                            edges nodefactor.deg.main.deg.pers.0.1 
##                       0.46877629                       0.48862449 
## nodefactor.deg.main.deg.pers.0.2 nodefactor.deg.main.deg.pers.1.0 
##                       0.30093219                       0.87066399 
## nodefactor.deg.main.deg.pers.1.1 nodefactor.deg.main.deg.pers.1.2 
##                       0.17485544                       0.41712816 
##              nodefactor.riskg.O3              nodefactor.riskg.O4 
##                       0.74375647                       0.62359340 
##              nodefactor.riskg.Y2              nodefactor.riskg.Y3 
##                       0.37265804                       0.32323771 
##            nodefactor.race..wa.B            nodefactor.race..wa.H 
##                       0.10188042                       0.20459658 
##             nodefactor.region.EW             nodefactor.region.OW 
##                       0.59805068                       0.67654404 
##             nodematch.race..wa.B             nodematch.race..wa.H 
##                       0.07479283                       0.04159744 
##             nodematch.race..wa.O                 nodematch.region 
##                       0.29989546                       0.97006818 
##                 absdiff.sqrt.age 
##                       0.03992758 
## Joint P-value (lower = worse):  0.06662289 .
## Chain 8 
## 
## Fraction in 1st window = 0.1
## Fraction in 2nd window = 0.5 
## 
##                            edges nodefactor.deg.main.deg.pers.0.1 
##                          0.46496                          0.08844 
## nodefactor.deg.main.deg.pers.0.2 nodefactor.deg.main.deg.pers.1.0 
##                         -0.23122                         -2.02242 
## nodefactor.deg.main.deg.pers.1.1 nodefactor.deg.main.deg.pers.1.2 
##                         -0.02396                          0.71062 
##              nodefactor.riskg.O3              nodefactor.riskg.O4 
##                          0.49024                         -0.21710 
##              nodefactor.riskg.Y2              nodefactor.riskg.Y3 
##                         -0.80488                          0.29206 
##            nodefactor.race..wa.B            nodefactor.race..wa.H 
##                         -0.05311                         -0.09563 
##             nodefactor.region.EW             nodefactor.region.OW 
##                         -0.06525                          0.52435 
##             nodematch.race..wa.B             nodematch.race..wa.H 
##                         -0.38021                         -0.14537 
##             nodematch.race..wa.O                 nodematch.region 
##                          0.36343                          0.22887 
##                 absdiff.sqrt.age 
##                          0.02275 
## 
## Individual P-values (lower = worse):
##                            edges nodefactor.deg.main.deg.pers.0.1 
##                       0.64196240                       0.92952591 
## nodefactor.deg.main.deg.pers.0.2 nodefactor.deg.main.deg.pers.1.0 
##                       0.81714423                       0.04313297 
## nodefactor.deg.main.deg.pers.1.1 nodefactor.deg.main.deg.pers.1.2 
##                       0.98088792                       0.47732203 
##              nodefactor.riskg.O3              nodefactor.riskg.O4 
##                       0.62396446                       0.82813159 
##              nodefactor.riskg.Y2              nodefactor.riskg.Y3 
##                       0.42088973                       0.77024296 
##            nodefactor.race..wa.B            nodefactor.race..wa.H 
##                       0.95764349                       0.92381699 
##             nodefactor.region.EW             nodefactor.region.OW 
##                       0.94797541                       0.60003712 
##             nodematch.race..wa.B             nodematch.race..wa.H 
##                       0.70379167                       0.88441849 
##             nodematch.race..wa.O                 nodematch.region 
##                       0.71628696                       0.81896616 
##                 absdiff.sqrt.age 
##                       0.98184777 
## Joint P-value (lower = worse):  0.992922 .
## Warning in formals(fun): argument is not a function

## 
## MCMC diagnostics shown here are from the last round of simulation, prior to computation of final parameter estimates. Because the final estimates are refinements of those used for this simulation run, these diagnostics may understate model performance. To directly assess the performance of the final model on in-model statistics, please use the GOF command: gof(ergmFitObject, GOF=~model).

Summary of model fit

Model 1

summary(est.i.buildup.bal[[1]])
## 
## ==========================
## Summary of model fit
## ==========================
## 
## Formula:   nw ~ edges + offset(nodematch("role.class", diff = TRUE, keep = 1:2))
## <environment: 0x556c7b13f3d8>
## 
## Iterations:  2 out of 400 
## 
## Monte Carlo MLE Results:
##                         Estimate Std. Error MCMC % p-value    
## edges                  -11.48559    0.04611      0  <1e-04 ***
## nodematch.role.class.I      -Inf    0.00000      0  <1e-04 ***
## nodematch.role.class.R      -Inf    0.00000      0  <1e-04 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Log-likelihood was not estimated for this fit.
## To get deviances, AIC, and/or BIC from fit `object$fit` run 
##   > object$fit<-logLik(object$fit, add=TRUE)
## to add it to the object or rerun this function with eval.loglik=TRUE.
## 
##  The following terms are fixed by offset and are not estimated:
##   nodematch.role.class.I nodematch.role.class.R 
## 
## 
## Dissolution Coefficients
## =======================
## Dissolution Model: ~offset(edges)
## Target Statistics: 1
## Crude Coefficient: -Inf
## Mortality/Exit Rate: 0
## Adjusted Coefficient: -Inf

Model 2

summary(est.i.buildup.bal[[2]])
## 
## ==========================
## Summary of model fit
## ==========================
## 
## Formula:   nw ~ edges + nodefactor("race..wa", base = 3) + offset(nodematch("role.class", 
##     diff = TRUE, keep = 1:2))
## <environment: 0x556c9649a898>
## 
## Iterations:  2 out of 400 
## 
## Monte Carlo MLE Results:
##                         Estimate Std. Error MCMC % p-value    
## edges                  -11.64961    0.05801      0 < 1e-04 ***
## nodefactor.race..wa.B    0.34253    0.12034      0 0.00442 ** 
## nodefactor.race..wa.H    0.44595    0.08955      0 < 1e-04 ***
## nodematch.role.class.I      -Inf    0.00000      0 < 1e-04 ***
## nodematch.role.class.R      -Inf    0.00000      0 < 1e-04 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Log-likelihood was not estimated for this fit.
## To get deviances, AIC, and/or BIC from fit `object$fit` run 
##   > object$fit<-logLik(object$fit, add=TRUE)
## to add it to the object or rerun this function with eval.loglik=TRUE.
## 
##  The following terms are fixed by offset and are not estimated:
##   nodematch.role.class.I nodematch.role.class.R 
## 
## 
## Dissolution Coefficients
## =======================
## Dissolution Model: ~offset(edges)
## Target Statistics: 1
## Crude Coefficient: -Inf
## Mortality/Exit Rate: 0
## Adjusted Coefficient: -Inf

Model 3

summary(est.i.buildup.bal[[3]])
## 
## ==========================
## Summary of model fit
## ==========================
## 
## Formula:   nw ~ edges + nodefactor("race..wa", base = 3) + nodematch("race..wa", 
##     diff = TRUE) + offset(nodematch("role.class", diff = TRUE, 
##     keep = 1:2))
## <environment: 0x556cac2e0988>
## 
## Iterations:  2 out of 400 
## 
## Monte Carlo MLE Results:
##                        Estimate Std. Error MCMC % p-value    
## edges                  -12.1460     0.2978      0 < 1e-04 ***
## nodefactor.race..wa.B    0.7670     0.2638      0 0.00364 ** 
## nodefactor.race..wa.H    0.8668     0.2806      0 0.00201 ** 
## nodematch.race..wa.B    -0.5082     0.6946      0 0.46439    
## nodematch.race..wa.H    -0.2128     0.4044      0 0.59882    
## nodematch.race..wa.O     0.5180     0.3036      0 0.08797 .  
## nodematch.role.class.I     -Inf     0.0000      0 < 1e-04 ***
## nodematch.role.class.R     -Inf     0.0000      0 < 1e-04 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Log-likelihood was not estimated for this fit.
## To get deviances, AIC, and/or BIC from fit `object$fit` run 
##   > object$fit<-logLik(object$fit, add=TRUE)
## to add it to the object or rerun this function with eval.loglik=TRUE.
## 
##  The following terms are fixed by offset and are not estimated:
##   nodematch.role.class.I nodematch.role.class.R 
## 
## 
## Dissolution Coefficients
## =======================
## Dissolution Model: ~offset(edges)
## Target Statistics: 1
## Crude Coefficient: -Inf
## Mortality/Exit Rate: 0
## Adjusted Coefficient: -Inf

Model 4

summary(est.i.buildup.bal[[4]])
## 
## ==========================
## Summary of model fit
## ==========================
## 
## Formula:   nw ~ edges + nodefactor(c("deg.main", "deg.pers")) + nodefactor("race..wa", 
##     base = 3) + nodematch("race..wa", diff = TRUE) + offset(nodematch("role.class", 
##     diff = TRUE, keep = 1:2))
## <environment: 0x556cc2386c30>
## 
## Iterations:  2 out of 400 
## 
## Monte Carlo MLE Results:
##                                   Estimate Std. Error MCMC % p-value    
## edges                            -11.91992    0.30551      0 < 1e-04 ***
## nodefactor.deg.main.deg.pers.0.1   0.80997    0.08953      0 < 1e-04 ***
## nodefactor.deg.main.deg.pers.0.2  -0.82193    0.17285      0 < 1e-04 ***
## nodefactor.deg.main.deg.pers.1.0  -2.24970    0.16908      0 < 1e-04 ***
## nodefactor.deg.main.deg.pers.1.1   0.80905    0.09903      0 < 1e-04 ***
## nodefactor.deg.main.deg.pers.1.2   0.76871    0.09601      0 < 1e-04 ***
## nodefactor.race..wa.B              0.76800    0.26498      0 0.00375 ** 
## nodefactor.race..wa.H              0.89139    0.28034      0 0.00147 ** 
## nodematch.race..wa.B              -0.51529    0.69568      0 0.45888    
## nodematch.race..wa.H              -0.21131    0.40417      0 0.60110    
## nodematch.race..wa.O               0.52019    0.30285      0 0.08586 .  
## nodematch.role.class.I                -Inf    0.00000      0 < 1e-04 ***
## nodematch.role.class.R                -Inf    0.00000      0 < 1e-04 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Log-likelihood was not estimated for this fit.
## To get deviances, AIC, and/or BIC from fit `object$fit` run 
##   > object$fit<-logLik(object$fit, add=TRUE)
## to add it to the object or rerun this function with eval.loglik=TRUE.
## 
##  The following terms are fixed by offset and are not estimated:
##   nodematch.role.class.I nodematch.role.class.R 
## 
## 
## Dissolution Coefficients
## =======================
## Dissolution Model: ~offset(edges)
## Target Statistics: 1
## Crude Coefficient: -Inf
## Mortality/Exit Rate: 0
## Adjusted Coefficient: -Inf

Model 5

summary(est.i.buildup.bal[[5]])
## 
## ==========================
## Summary of model fit
## ==========================
## 
## Formula:   nw ~ edges + nodefactor(c("deg.main", "deg.pers")) + nodefactor("race..wa", 
##     base = 3) + nodefactor("region", base = 2) + nodematch("race..wa", 
##     diff = TRUE) + offset(nodematch("role.class", diff = TRUE, 
##     keep = 1:2))
## <environment: 0x556cd86d05a8>
## 
## Iterations:  2 out of 400 
## 
## Monte Carlo MLE Results:
##                                   Estimate Std. Error MCMC % p-value    
## edges                            -11.64816    0.30809      0 < 1e-04 ***
## nodefactor.deg.main.deg.pers.0.1   0.81259    0.08956      0 < 1e-04 ***
## nodefactor.deg.main.deg.pers.0.2  -0.81563    0.17163      0 < 1e-04 ***
## nodefactor.deg.main.deg.pers.1.0  -2.24239    0.16865      0 < 1e-04 ***
## nodefactor.deg.main.deg.pers.1.1   0.81298    0.09851      0 < 1e-04 ***
## nodefactor.deg.main.deg.pers.1.2   0.75928    0.09624      0 < 1e-04 ***
## nodefactor.race..wa.B              0.72389    0.26465      0 0.00623 ** 
## nodefactor.race..wa.H              0.90240    0.28016      0 0.00128 ** 
## nodefactor.region.EW              -0.28407    0.11808      0 0.01614 *  
## nodefactor.region.OW              -0.37400    0.07505      0 < 1e-04 ***
## nodematch.race..wa.B              -0.51135    0.68682      0 0.45656    
## nodematch.race..wa.H              -0.21086    0.40040      0 0.59845    
## nodematch.race..wa.O               0.51962    0.30260      0 0.08595 .  
## nodematch.role.class.I                -Inf    0.00000      0 < 1e-04 ***
## nodematch.role.class.R                -Inf    0.00000      0 < 1e-04 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Log-likelihood was not estimated for this fit.
## To get deviances, AIC, and/or BIC from fit `object$fit` run 
##   > object$fit<-logLik(object$fit, add=TRUE)
## to add it to the object or rerun this function with eval.loglik=TRUE.
## 
##  The following terms are fixed by offset and are not estimated:
##   nodematch.role.class.I nodematch.role.class.R 
## 
## 
## Dissolution Coefficients
## =======================
## Dissolution Model: ~offset(edges)
## Target Statistics: 1
## Crude Coefficient: -Inf
## Mortality/Exit Rate: 0
## Adjusted Coefficient: -Inf

Model 6

summary(est.i.buildup.bal[[6]])
## 
## ==========================
## Summary of model fit
## ==========================
## 
## Formula:   nw ~ edges + nodefactor(c("deg.main", "deg.pers")) + nodefactor("race..wa", 
##     base = 3) + nodefactor("region", base = 2) + nodematch("race..wa", 
##     diff = TRUE) + absdiff("sqrt.age") + offset(nodematch("role.class", 
##     diff = TRUE, keep = 1:2))
## <environment: 0x556cef616e80>
## 
## Iterations:  2 out of 400 
## 
## Monte Carlo MLE Results:
##                                   Estimate Std. Error MCMC % p-value    
## edges                            -11.03749    0.31295      0 < 1e-04 ***
## nodefactor.deg.main.deg.pers.0.1   0.80724    0.08963      0 < 1e-04 ***
## nodefactor.deg.main.deg.pers.0.2  -0.81455    0.17296      0 < 1e-04 ***
## nodefactor.deg.main.deg.pers.1.0  -2.24844    0.16825      0 < 1e-04 ***
## nodefactor.deg.main.deg.pers.1.1   0.80391    0.09880      0 < 1e-04 ***
## nodefactor.deg.main.deg.pers.1.2   0.76688    0.09632      0 < 1e-04 ***
## nodefactor.race..wa.B              0.73962    0.26273      0 0.00488 ** 
## nodefactor.race..wa.H              0.90781    0.27994      0 0.00118 ** 
## nodefactor.region.EW              -0.28654    0.11694      0 0.01427 *  
## nodefactor.region.OW              -0.37857    0.07530      0 < 1e-04 ***
## nodematch.race..wa.B              -0.51022    0.68917      0 0.45909    
## nodematch.race..wa.H              -0.20857    0.40390      0 0.60558    
## nodematch.race..wa.O               0.51717    0.30200      0 0.08681 .  
## absdiff.sqrt.age                  -0.63434    0.06817      0 < 1e-04 ***
## nodematch.role.class.I                -Inf    0.00000      0 < 1e-04 ***
## nodematch.role.class.R                -Inf    0.00000      0 < 1e-04 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Log-likelihood was not estimated for this fit.
## To get deviances, AIC, and/or BIC from fit `object$fit` run 
##   > object$fit<-logLik(object$fit, add=TRUE)
## to add it to the object or rerun this function with eval.loglik=TRUE.
## 
##  The following terms are fixed by offset and are not estimated:
##   nodematch.role.class.I nodematch.role.class.R 
## 
## 
## Dissolution Coefficients
## =======================
## Dissolution Model: ~offset(edges)
## Target Statistics: 1
## Crude Coefficient: -Inf
## Mortality/Exit Rate: 0
## Adjusted Coefficient: -Inf

Model 7

summary(est.i.buildup.bal[[7]])
## 
## ==========================
## Summary of model fit
## ==========================
## 
## Formula:   nw ~ edges + nodefactor(c("deg.main", "deg.pers")) + nodefactor("riskg", 
##     base = 8) + nodefactor("race..wa", base = 3) + nodefactor("region", 
##     base = 2) + nodematch("race..wa", diff = TRUE) + absdiff("sqrt.age") + 
##     offset(nodematch("role.class", diff = TRUE, keep = 1:2))
## <environment: 0x556d06781378>
## 
## Iterations:  2 out of 400 
## 
## Monte Carlo MLE Results:
##                                  Estimate Std. Error MCMC %  p-value    
## edges                            -8.29452    0.31519      0  < 1e-04 ***
## nodefactor.deg.main.deg.pers.0.1  0.85430    0.09032      0  < 1e-04 ***
## nodefactor.deg.main.deg.pers.0.2 -0.80260    0.17194      0  < 1e-04 ***
## nodefactor.deg.main.deg.pers.1.0 -2.29710    0.16895      0  < 1e-04 ***
## nodefactor.deg.main.deg.pers.1.1  0.81692    0.09858      0  < 1e-04 ***
## nodefactor.deg.main.deg.pers.1.2  0.76436    0.09618      0  < 1e-04 ***
## nodefactor.riskg.O1                  -Inf    0.00000      0  < 1e-04 ***
## nodefactor.riskg.O2                  -Inf    0.00000      0  < 1e-04 ***
## nodefactor.riskg.O3              -3.35098    0.38165      0  < 1e-04 ***
## nodefactor.riskg.O4              -0.49646    0.09688      0  < 1e-04 ***
## nodefactor.riskg.Y1                  -Inf    0.00000      0  < 1e-04 ***
## nodefactor.riskg.Y2              -4.57088    0.35213      0  < 1e-04 ***
## nodefactor.riskg.Y3              -2.38162    0.12516      0  < 1e-04 ***
## nodefactor.race..wa.B             0.69617    0.26577      0 0.008806 ** 
## nodefactor.race..wa.H             1.00140    0.28157      0 0.000376 ***
## nodefactor.region.EW             -0.33932    0.11695      0 0.003716 ** 
## nodefactor.region.OW             -0.42416    0.07598      0  < 1e-04 ***
## nodematch.race..wa.B             -0.50139    0.67485      0 0.457502    
## nodematch.race..wa.H             -0.20522    0.40389      0 0.611371    
## nodematch.race..wa.O              0.51762    0.30274      0 0.087309 .  
## absdiff.sqrt.age                 -0.58168    0.07146      0  < 1e-04 ***
## nodematch.role.class.I               -Inf    0.00000      0  < 1e-04 ***
## nodematch.role.class.R               -Inf    0.00000      0  < 1e-04 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Log-likelihood was not estimated for this fit.
## To get deviances, AIC, and/or BIC from fit `object$fit` run 
##   > object$fit<-logLik(object$fit, add=TRUE)
## to add it to the object or rerun this function with eval.loglik=TRUE.
## 
##  Warning: The following terms have infinite coefficient estimates:
##   nodefactor.riskg.O1 nodefactor.riskg.O2 nodefactor.riskg.Y1 
## 
##  The following terms are fixed by offset and are not estimated:
##   nodematch.role.class.I nodematch.role.class.R 
## 
## 
## Dissolution Coefficients
## =======================
## Dissolution Model: ~offset(edges)
## Target Statistics: 1
## Crude Coefficient: -Inf
## Mortality/Exit Rate: 0
## Adjusted Coefficient: -Inf

Model 8

summary(est.i.buildup.bal[[8]])
## 
## ==========================
## Summary of model fit
## ==========================
## 
## Formula:   nw ~ edges + nodefactor(c("deg.main", "deg.pers")) + nodefactor("riskg", 
##     base = 8) + nodefactor("race..wa", base = 3) + nodefactor("region", 
##     base = 2) + nodematch("race..wa", diff = TRUE) + nodematch("region", 
##     diff = FALSE) + absdiff("sqrt.age") + offset(nodematch("role.class", 
##     diff = TRUE, keep = 1:2))
## <environment: 0x556d232e8688>
## 
## Iterations:  2 out of 400 
## 
## Monte Carlo MLE Results:
##                                  Estimate Std. Error MCMC % p-value    
## edges                            -9.76545    0.33238      0 < 1e-04 ***
## nodefactor.deg.main.deg.pers.0.1  0.85374    0.09042      0 < 1e-04 ***
## nodefactor.deg.main.deg.pers.0.2 -0.80116    0.17060      0 < 1e-04 ***
## nodefactor.deg.main.deg.pers.1.0 -2.29803    0.16813      0 < 1e-04 ***
## nodefactor.deg.main.deg.pers.1.1  0.81539    0.09900      0 < 1e-04 ***
## nodefactor.deg.main.deg.pers.1.2  0.76475    0.09580      0 < 1e-04 ***
## nodefactor.riskg.O1                  -Inf    0.00000      0 < 1e-04 ***
## nodefactor.riskg.O2                  -Inf    0.00000      0 < 1e-04 ***
## nodefactor.riskg.O3              -3.35146    0.37521      0 < 1e-04 ***
## nodefactor.riskg.O4              -0.49466    0.09661      0 < 1e-04 ***
## nodefactor.riskg.Y1                  -Inf    0.00000      0 < 1e-04 ***
## nodefactor.riskg.Y2              -4.56734    0.35403      0 < 1e-04 ***
## nodefactor.riskg.Y3              -2.38089    0.12353      0 < 1e-04 ***
## nodefactor.race..wa.B             0.70670    0.26505      0 0.00767 ** 
## nodefactor.race..wa.H             1.01286    0.28083      0 0.00031 ***
## nodefactor.region.EW              0.39892    0.10124      0 < 1e-04 ***
## nodefactor.region.OW             -0.04416    0.06108      0 0.46970    
## nodematch.race..wa.B             -0.49211    0.58378      0 0.39924    
## nodematch.race..wa.H             -0.25247    0.40274      0 0.53073    
## nodematch.race..wa.O              0.52455    0.30237      0 0.08277 .  
## nodematch.region                  1.74122    0.12080      0 < 1e-04 ***
## absdiff.sqrt.age                 -0.58090    0.07141      0 < 1e-04 ***
## nodematch.role.class.I               -Inf    0.00000      0 < 1e-04 ***
## nodematch.role.class.R               -Inf    0.00000      0 < 1e-04 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Log-likelihood was not estimated for this fit.
## To get deviances, AIC, and/or BIC from fit `object$fit` run 
##   > object$fit<-logLik(object$fit, add=TRUE)
## to add it to the object or rerun this function with eval.loglik=TRUE.
## 
##  Warning: The following terms have infinite coefficient estimates:
##   nodefactor.riskg.O1 nodefactor.riskg.O2 nodefactor.riskg.Y1 
## 
##  The following terms are fixed by offset and are not estimated:
##   nodematch.role.class.I nodematch.role.class.R 
## 
## 
## Dissolution Coefficients
## =======================
## Dissolution Model: ~offset(edges)
## Target Statistics: 1
## Crude Coefficient: -Inf
## Mortality/Exit Rate: 0
## Adjusted Coefficient: -Inf

Network diagnostics

Model 1

(dx_inst1 <- netdx(est.i.buildup.bal[[1]], nsims = 10, nsteps = 1000, ncores = 4, nwstats.formula = est.i.buildup.bal[[8]]$formation, set.control.ergm = control.simulate.ergm(MCMC.interval = 1e+5, MCMC.burnin = 1e+6)))
## 
## Network Diagnostics
## -----------------------
## - Simulating 10 networks
## - Calculating formation statistics
## - Calculating duration statistics
## - Calculating dissolution statistics
## 
## EpiModel Network Diagnostics
## =======================
## Diagnostic Method: Dynamic
## Simulations: 10
## Time Steps per Sim: 1000
## 
## Formation Diagnostics
## ----------------------- 
##                                   Target Sim Mean Pct Diff Sim SD
## edges                            479.159  478.942        0 21.864
## nodefactor.deg.main.deg.pers.0.1      NA   68.959       NA  8.630
## nodefactor.deg.main.deg.pers.0.2      NA   73.286       NA  8.868
## nodefactor.deg.main.deg.pers.1.0      NA  318.038       NA 20.482
## nodefactor.deg.main.deg.pers.1.1      NA   52.675       NA  7.379
## nodefactor.deg.main.deg.pers.1.2      NA   59.214       NA  7.890
## nodefactor.riskg.O1                   NA   55.032       NA  7.645
## nodefactor.riskg.O2                   NA   54.500       NA  7.704
## nodefactor.riskg.O3                   NA   55.073       NA  7.668
## nodefactor.riskg.O4                   NA   54.616       NA  7.524
## nodefactor.riskg.Y1                   NA  185.155       NA 14.963
## nodefactor.riskg.Y2                   NA  184.723       NA 14.845
## nodefactor.riskg.Y3                   NA  184.328       NA 14.883
## nodefactor.race..wa.B                 NA   58.282       NA  7.867
## nodefactor.race..wa.H                 NA  103.830       NA 10.747
## nodefactor.region.EW                  NA   96.303       NA 10.372
## nodefactor.region.OW                  NA  315.003       NA 20.445
## nodematch.race..wa.B                  NA    1.776       NA  1.341
## nodematch.race..wa.H                  NA    5.614       NA  2.386
## nodematch.race..wa.O                  NA  330.571       NA 18.219
## nodematch.region                      NA  212.589       NA 14.381
## absdiff.sqrt.age                      NA  546.206       NA 30.353
## nodematch.role.class.I                NA    0.000       NA  0.000
## nodematch.role.class.R                NA    0.000       NA  0.000
## 
## Dissolution Diagnostics
## ----------------------- 
##                Target Sim Mean Pct Diff Sim SD
## Edge Duration       1        1        0      0
## Pct Edges Diss      1        1        0      0
plot(dx_inst1, type="formation")

plot(dx_inst1, type="duration")

plot(dx_inst1, type="dissolution")

Model 2

(dx_inst2 <- netdx(est.i.buildup.bal[[2]], nsims = 10, nsteps = 1000, ncores = 4, nwstats.formula = est.i.buildup.bal[[8]]$formation, set.control.ergm = control.simulate.ergm(MCMC.interval = 1e+5, MCMC.burnin = 1e+6)))
## 
## Network Diagnostics
## -----------------------
## - Simulating 10 networks
## - Calculating formation statistics
## - Calculating duration statistics
## - Calculating dissolution statistics
## 
## EpiModel Network Diagnostics
## =======================
## Diagnostic Method: Dynamic
## Simulations: 10
## Time Steps per Sim: 1000
## 
## Formation Diagnostics
## ----------------------- 
##                                   Target Sim Mean Pct Diff Sim SD
## edges                            479.159  478.973    0.000 21.884
## nodefactor.deg.main.deg.pers.0.1      NA   68.037       NA  8.597
## nodefactor.deg.main.deg.pers.0.2      NA   73.537       NA  8.900
## nodefactor.deg.main.deg.pers.1.0      NA  319.829       NA 20.656
## nodefactor.deg.main.deg.pers.1.1      NA   53.478       NA  7.500
## nodefactor.deg.main.deg.pers.1.2      NA   59.681       NA  7.958
## nodefactor.riskg.O1                   NA   55.447       NA  7.543
## nodefactor.riskg.O2                   NA   54.878       NA  7.546
## nodefactor.riskg.O3                   NA   53.903       NA  7.594
## nodefactor.riskg.O4                   NA   55.133       NA  7.665
## nodefactor.riskg.Y1                   NA  185.527       NA 14.778
## nodefactor.riskg.Y2                   NA  185.305       NA 14.948
## nodefactor.riskg.Y3                   NA  183.054       NA 14.861
## nodefactor.race..wa.B             75.591   75.529   -0.001  9.002
## nodefactor.race..wa.H            149.174  148.932   -0.002 13.184
## nodefactor.region.EW                  NA  100.538       NA 10.526
## nodefactor.region.OW                  NA  311.499       NA 20.040
## nodematch.race..wa.B                  NA    2.960       NA  1.728
## nodematch.race..wa.H                  NA   11.528       NA  3.384
## nodematch.race..wa.O                  NA  280.750       NA 16.636
## nodematch.region                      NA  211.392       NA 14.588
## absdiff.sqrt.age                      NA  546.654       NA 30.383
## nodematch.role.class.I                NA    0.000       NA  0.000
## nodematch.role.class.R                NA    0.000       NA  0.000
## 
## Dissolution Diagnostics
## ----------------------- 
##                Target Sim Mean Pct Diff Sim SD
## Edge Duration       1        1        0      0
## Pct Edges Diss      1        1        0      0
plot(dx_inst2, type="formation")

plot(dx_inst2, type="duration")

plot(dx_inst2, type="dissolution")

Model 3

(dx_inst3 <- netdx(est.i.buildup.bal[[3]], nsims = 10, nsteps = 1000, ncores = 4, nwstats.formula = est.i.buildup.bal[[8]]$formation, set.control.ergm = control.simulate.ergm(MCMC.interval = 1e+5, MCMC.burnin = 1e+6)))
## 
## Network Diagnostics
## -----------------------
## - Simulating 10 networks
## - Calculating formation statistics
## - Calculating duration statistics
## - Calculating dissolution statistics
## 
## EpiModel Network Diagnostics
## =======================
## Diagnostic Method: Dynamic
## Simulations: 10
## Time Steps per Sim: 1000
## 
## Formation Diagnostics
## ----------------------- 
##                                   Target Sim Mean Pct Diff Sim SD
## edges                            479.159  478.741   -0.001 21.607
## nodefactor.deg.main.deg.pers.0.1      NA   68.189       NA  8.564
## nodefactor.deg.main.deg.pers.0.2      NA   73.463       NA  8.900
## nodefactor.deg.main.deg.pers.1.0      NA  319.687       NA 20.499
## nodefactor.deg.main.deg.pers.1.1      NA   53.479       NA  7.374
## nodefactor.deg.main.deg.pers.1.2      NA   59.961       NA  8.037
## nodefactor.riskg.O1                   NA   55.349       NA  7.693
## nodefactor.riskg.O2                   NA   54.779       NA  7.573
## nodefactor.riskg.O3                   NA   53.985       NA  7.552
## nodefactor.riskg.O4                   NA   55.005       NA  7.565
## nodefactor.riskg.Y1                   NA  185.369       NA 14.828
## nodefactor.riskg.Y2                   NA  185.078       NA 14.783
## nodefactor.riskg.Y3                   NA  183.099       NA 14.760
## nodefactor.race..wa.B             75.591   75.170   -0.006  8.902
## nodefactor.race..wa.H            149.174  148.307   -0.006 13.172
## nodefactor.region.EW                  NA  100.468       NA 10.581
## nodefactor.region.OW                  NA  311.128       NA 19.931
## nodematch.race..wa.B               2.540    2.522   -0.007  1.574
## nodematch.race..wa.H              13.269   13.023   -0.019  3.598
## nodematch.race..wa.O             286.880  287.085    0.001 16.938
## nodematch.region                      NA  211.313       NA 14.567
## absdiff.sqrt.age                      NA  546.386       NA 30.294
## nodematch.role.class.I                NA    0.000       NA  0.000
## nodematch.role.class.R                NA    0.000       NA  0.000
## 
## Dissolution Diagnostics
## ----------------------- 
##                Target Sim Mean Pct Diff Sim SD
## Edge Duration       1        1        0      0
## Pct Edges Diss      1        1        0      0
plot(dx_inst3, type="formation")

plot(dx_inst3, type="duration")

plot(dx_inst3, type="dissolution")

Model 4

(dx_inst4 <- netdx(est.i.buildup.bal[[4]], nsims = 10, nsteps = 1000, ncores = 4, nwstats.formula = est.i.buildup.bal[[8]]$formation, set.control.ergm = control.simulate.ergm(MCMC.interval = 1e+5, MCMC.burnin = 1e+6)))
## 
## Network Diagnostics
## -----------------------
## - Simulating 10 networks
## - Calculating formation statistics
## - Calculating duration statistics
## - Calculating dissolution statistics
## 
## EpiModel Network Diagnostics
## =======================
## Diagnostic Method: Dynamic
## Simulations: 10
## Time Steps per Sim: 1000
## 
## Formation Diagnostics
## ----------------------- 
##                                   Target Sim Mean Pct Diff Sim SD
## edges                            479.159  462.628   -0.034 22.651
## nodefactor.deg.main.deg.pers.0.1 172.310  161.548   -0.062 14.461
## nodefactor.deg.main.deg.pers.0.2  36.371   36.336   -0.001  6.170
## nodefactor.deg.main.deg.pers.1.0  38.033   38.027    0.000  6.331
## nodefactor.deg.main.deg.pers.1.1 135.538  125.975   -0.071 12.340
## nodefactor.deg.main.deg.pers.1.2 145.388  135.961   -0.065 12.986
## nodefactor.riskg.O1                   NA   55.547       NA  7.709
## nodefactor.riskg.O2                   NA   52.419       NA  7.550
## nodefactor.riskg.O3                   NA   54.915       NA  7.720
## nodefactor.riskg.O4                   NA   50.661       NA  7.290
## nodefactor.riskg.Y1                   NA  177.157       NA 15.012
## nodefactor.riskg.Y2                   NA  181.282       NA 14.861
## nodefactor.riskg.Y3                   NA  176.444       NA 14.783
## nodefactor.race..wa.B             75.591   71.189   -0.058  8.958
## nodefactor.race..wa.H            149.174  137.012   -0.082 13.159
## nodefactor.region.EW                  NA   92.564       NA 10.169
## nodefactor.region.OW                  NA  298.352       NA 20.408
## nodematch.race..wa.B               2.540    2.431   -0.043  1.569
## nodematch.race..wa.H              13.269   11.196   -0.156  3.399
## nodematch.race..wa.O             286.880  282.096   -0.017 17.198
## nodematch.region                      NA  207.076       NA 14.775
## absdiff.sqrt.age                      NA  529.015       NA 31.295
## nodematch.role.class.I                NA    0.000       NA  0.000
## nodematch.role.class.R                NA    0.000       NA  0.000
## 
## Dissolution Diagnostics
## ----------------------- 
##                Target Sim Mean Pct Diff Sim SD
## Edge Duration       1        1        0      0
## Pct Edges Diss      1        1        0      0
plot(dx_inst4, type="formation")

plot(dx_inst4, type="duration")

plot(dx_inst4, type="dissolution")

Model 5

(dx_inst5 <- netdx(est.i.buildup.bal[[5]], nsims = 10, nsteps = 1000, ncores = 4, nwstats.formula = est.i.buildup.bal[[8]]$formation, set.control.ergm = control.simulate.ergm(MCMC.interval = 1e+5, MCMC.burnin = 1e+6)))
## 
## Network Diagnostics
## -----------------------
## - Simulating 10 networks
## - Calculating formation statistics
## - Calculating duration statistics
## - Calculating dissolution statistics
## 
## EpiModel Network Diagnostics
## =======================
## Diagnostic Method: Dynamic
## Simulations: 10
## Time Steps per Sim: 1000
## 
## Formation Diagnostics
## ----------------------- 
##                                   Target Sim Mean Pct Diff Sim SD
## edges                            479.159  459.595   -0.041 22.929
## nodefactor.deg.main.deg.pers.0.1 172.310  159.624   -0.074 14.435
## nodefactor.deg.main.deg.pers.0.2  36.371   36.330   -0.001  6.108
## nodefactor.deg.main.deg.pers.1.0  38.033   38.058    0.001  6.394
## nodefactor.deg.main.deg.pers.1.1 135.538  124.780   -0.079 12.527
## nodefactor.deg.main.deg.pers.1.2 145.388  134.809   -0.073 13.006
## nodefactor.riskg.O1                   NA   55.198       NA  7.757
## nodefactor.riskg.O2                   NA   52.914       NA  7.573
## nodefactor.riskg.O3                   NA   54.757       NA  7.681
## nodefactor.riskg.O4                   NA   50.174       NA  7.251
## nodefactor.riskg.Y1                   NA  175.215       NA 14.727
## nodefactor.riskg.Y2                   NA  180.132       NA 15.067
## nodefactor.riskg.Y3                   NA  175.657       NA 14.893
## nodefactor.race..wa.B             75.591   70.350   -0.069  8.916
## nodefactor.race..wa.H            149.174  135.580   -0.091 13.236
## nodefactor.region.EW              83.501   80.465   -0.036  9.587
## nodefactor.region.OW             242.486  237.429   -0.021 17.263
## nodematch.race..wa.B               2.540    2.412   -0.050  1.558
## nodematch.race..wa.H              13.269   10.973   -0.173  3.360
## nodematch.race..wa.O             286.880  280.806   -0.021 17.094
## nodematch.region                      NA  230.345       NA 15.966
## absdiff.sqrt.age                      NA  525.807       NA 31.532
## nodematch.role.class.I                NA    0.000       NA  0.000
## nodematch.role.class.R                NA    0.000       NA  0.000
## 
## Dissolution Diagnostics
## ----------------------- 
##                Target Sim Mean Pct Diff Sim SD
## Edge Duration       1        1        0      0
## Pct Edges Diss      1        1        0      0
plot(dx_inst5, type="formation")

plot(dx_inst5, type="duration")

plot(dx_inst5, type="dissolution")

Model 6

(dx_inst6 <- netdx(est.i.buildup.bal[[6]], nsims = 10, nsteps = 1000, ncores = 4, nwstats.formula = est.i.buildup.bal[[8]]$formation, set.control.ergm = control.simulate.ergm(MCMC.interval = 1e+5, MCMC.burnin = 1e+6)))
## 
## Network Diagnostics
## -----------------------
## - Simulating 10 networks
## - Calculating formation statistics
## - Calculating duration statistics
## - Calculating dissolution statistics
## 
## EpiModel Network Diagnostics
## =======================
## Diagnostic Method: Dynamic
## Simulations: 10
## Time Steps per Sim: 1000
## 
## Formation Diagnostics
## ----------------------- 
##                                   Target Sim Mean Pct Diff Sim SD
## edges                            479.159  451.820   -0.057 23.336
## nodefactor.deg.main.deg.pers.0.1 172.310  155.220   -0.099 14.474
## nodefactor.deg.main.deg.pers.0.2  36.371   36.400    0.001  6.179
## nodefactor.deg.main.deg.pers.1.0  38.033   37.966   -0.002  6.299
## nodefactor.deg.main.deg.pers.1.1 135.538  121.413   -0.104 12.412
## nodefactor.deg.main.deg.pers.1.2 145.388  130.729   -0.101 13.035
## nodefactor.riskg.O1                   NA   50.322       NA  7.559
## nodefactor.riskg.O2                   NA   48.384       NA  7.377
## nodefactor.riskg.O3                   NA   49.771       NA  7.484
## nodefactor.riskg.O4                   NA   45.491       NA  7.170
## nodefactor.riskg.Y1                   NA  176.298       NA 15.033
## nodefactor.riskg.Y2                   NA  180.726       NA 15.283
## nodefactor.riskg.Y3                   NA  176.681       NA 15.000
## nodefactor.race..wa.B             75.591   68.972   -0.088  8.845
## nodefactor.race..wa.H            149.174  132.074   -0.115 13.091
## nodefactor.region.EW              83.501   79.407   -0.049  9.346
## nodefactor.region.OW             242.486  234.601   -0.033 17.461
## nodematch.race..wa.B               2.540    2.342   -0.078  1.533
## nodematch.race..wa.H              13.269   10.534   -0.206  3.312
## nodematch.race..wa.O             286.880  276.963   -0.035 17.385
## nodematch.region                      NA  225.600       NA 16.046
## absdiff.sqrt.age                 380.500  368.339   -0.032 22.986
## nodematch.role.class.I                NA    0.000       NA  0.000
## nodematch.role.class.R                NA    0.000       NA  0.000
## 
## Dissolution Diagnostics
## ----------------------- 
##                Target Sim Mean Pct Diff Sim SD
## Edge Duration       1        1        0      0
## Pct Edges Diss      1        1        0      0
plot(dx_inst6, type="formation")

plot(dx_inst6, type="duration")

plot(dx_inst6, type="dissolution")

Model 7

(dx_inst7 <- netdx(est.i.buildup.bal[[7]], nsims = 10, nsteps = 1000, ncores = 4, set.control.ergm = control.simulate.ergm(MCMC.interval = 1e+5, MCMC.burnin = 1e+6)))
## 
## Network Diagnostics
## -----------------------
## - Simulating 10 networks
## - Calculating formation statistics
## - Calculating duration statistics
## - Calculating dissolution statistics
## 
## EpiModel Network Diagnostics
## =======================
## Diagnostic Method: Dynamic
## Simulations: 10
## Time Steps per Sim: 1000
## 
## Formation Diagnostics
## ----------------------- 
##                                   Target Sim Mean Pct Diff Sim SD
## edges                            479.159  237.216   -0.505 32.047
## nodefactor.deg.main.deg.pers.0.1 172.310   65.856   -0.618 12.887
## nodefactor.deg.main.deg.pers.0.2  36.371   26.579   -0.269  5.809
## nodefactor.deg.main.deg.pers.1.0  38.033   36.380   -0.043  6.196
## nodefactor.deg.main.deg.pers.1.1 135.538   51.622   -0.619 10.442
## nodefactor.deg.main.deg.pers.1.2 145.388   56.272   -0.613 11.096
## nodefactor.riskg.O1                   NA    0.000       NA  0.000
## nodefactor.riskg.O2                   NA    0.000       NA  0.000
## nodefactor.riskg.O3                6.856    6.787   -0.010  2.605
## nodefactor.riskg.O4              109.513   64.520   -0.411 11.540
## nodefactor.riskg.Y1                   NA    0.000       NA  0.000
## nodefactor.riskg.Y2                8.202    8.226    0.003  2.865
## nodefactor.riskg.Y3               70.786   64.635   -0.087  8.767
## nodefactor.race..wa.B             75.591   33.804   -0.553  7.440
## nodefactor.race..wa.H            149.174   61.481   -0.588 11.451
## nodefactor.region.EW              83.501   43.220   -0.482  8.423
## nodefactor.region.OW             242.486  133.560   -0.449 19.858
## nodematch.race..wa.B               2.540    1.125   -0.557  1.077
## nodematch.race..wa.H              13.269    4.287   -0.677  2.155
## nodematch.race..wa.O             286.880  152.625   -0.468 21.400
## absdiff.sqrt.age                 380.500  214.889   -0.435 29.213
## nodematch.role.class.I                NA    0.000       NA  0.000
## nodematch.role.class.R                NA    0.000       NA  0.000
## 
## Dissolution Diagnostics
## ----------------------- 
##                Target Sim Mean Pct Diff Sim SD
## Edge Duration       1        1        0      0
## Pct Edges Diss      1        1        0      0
plot(dx_inst7, type="formation")

plot(dx_inst7, type="duration")

plot(dx_inst7, type="dissolution")

Model 8

(dx_inst8 <- netdx(est.i.buildup.bal[[8]], nsims = 10, nsteps = 1000, ncores = 4, set.control.ergm = control.simulate.ergm(MCMC.interval = 1e+5, MCMC.burnin = 1e+6)))
## 
## Network Diagnostics
## -----------------------
## - Simulating 10 networks
## - Calculating formation statistics
## - Calculating duration statistics
## - Calculating dissolution statistics
## 
## EpiModel Network Diagnostics
## =======================
## Diagnostic Method: Dynamic
## Simulations: 10
## Time Steps per Sim: 1000
## 
## Formation Diagnostics
## ----------------------- 
##                                   Target Sim Mean Pct Diff Sim SD
## edges                            479.159  212.692   -0.556 29.753
## nodefactor.deg.main.deg.pers.0.1 172.310   58.543   -0.660 11.758
## nodefactor.deg.main.deg.pers.0.2  36.371   23.873   -0.344  5.567
## nodefactor.deg.main.deg.pers.1.0  38.033   34.615   -0.090  6.157
## nodefactor.deg.main.deg.pers.1.1 135.538   45.990   -0.661  9.603
## nodefactor.deg.main.deg.pers.1.2 145.388   50.342   -0.654 10.445
## nodefactor.riskg.O1                   NA    0.000       NA  0.000
## nodefactor.riskg.O2                   NA    0.000       NA  0.000
## nodefactor.riskg.O3                6.856    6.680   -0.026  2.616
## nodefactor.riskg.O4              109.513   57.231   -0.477 10.782
## nodefactor.riskg.Y1                   NA    0.000       NA  0.000
## nodefactor.riskg.Y2                8.202    8.171   -0.004  2.873
## nodefactor.riskg.Y3               70.786   60.666   -0.143  8.865
## nodefactor.race..wa.B             75.591   30.421   -0.598  6.915
## nodefactor.race..wa.H            149.174   54.687   -0.633 10.686
## nodefactor.region.EW              83.501   36.506   -0.563  8.070
## nodefactor.region.OW             242.486  117.689   -0.515 19.219
## nodematch.race..wa.B               2.540    1.046   -0.588  1.034
## nodematch.race..wa.H              13.269    3.799   -0.714  2.039
## nodematch.race..wa.O             286.880  137.155   -0.522 19.958
## nodematch.region                 383.327  145.866   -0.619 23.260
## absdiff.sqrt.age                 380.500  193.062   -0.493 27.552
## nodematch.role.class.I                NA    0.000       NA  0.000
## nodematch.role.class.R                NA    0.000       NA  0.000
## 
## Dissolution Diagnostics
## ----------------------- 
##                Target Sim Mean Pct Diff Sim SD
## Edge Duration       1        1        0      0
## Pct Edges Diss      1        1        0      0
plot(dx_inst8, type="formation")

plot(dx_inst8, type="duration")

plot(dx_inst8, type="dissolution")